Description
The globalization of the financial markets and outlines some of the major factors that are responsible for the emergence of the global economy.
Trend
Forecasting
With
Technical
Analysis
Trend
Forecasting
With
Technical
Analysis
UNLEASHING THE HIDDEN POWER OF INTERMARKET
ANALYSIS TO BEAT THE MARKET
LOUIS B. MENDELSOHN
FORWORD BY JOHN J. MURPHY
T R A D E S E C R E T S
Trend
Forecasting
With Technical
Analysis
Unleashing the Hidden Power
of Intermarket Analysis
to Beat the Market
BY LOUI S B. ME NDE L S OHN
Foreword by
John J. Murphy
Titles in the
Trade Secrets Series
Trend Forecasting With Technical Analysis:
Unleashing the Hidden Power of
Intermarket Analysis to Beat the Market
by Louis B. Mendelsohn
7 Chart Patterns That Consistently Make
Money by Ed Downs
Charting Made Easy by John Murphy
The Four Biggest Mistakes in Futures Trading
by Jay Kaeppel
The Four Biggest Mistakes in Options Trading
by Jay Kaeppel
Bar Chart Basics by Darrell Jobman
Trading System Secrets: Selecting a Winning
System by Joe Krutsinger
Profit Strategies: Unlocking Trading
Performance with Money Management
by David Stendahl
Simple Asset Allocation Strategies
by Roger Gibson
“Intermarket analysis tools —that build and
expand upon the single-market analysis methods
which defined technical analysis in the late
20th century —demand serious attention.”
— Louis B. Mendelsohn
Copyright © 2000 Market Technologies Corporation
Published by Marketplace Books
All rights reserved.
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trademarks of Market Technologies Corporation. “Synergistic Market Analysis,” “Synergistic Analysis” and
“Market Synergy” are trademarks of Louis B. Mendelsohn. “Investor’s Business Daily” is a registered trade-
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Technical Analysis, Inc. “Standard & Poor’s 500” is a trademark of The McGraw-Hill Companies, Inc. “S&P
500” and “S&P 100” are registered trademarks of The McGraw-Hill Companies, Inc. “Nikkei Stock Average”
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ISBN 1-883272-91-2
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Contents
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Chapter 1
TRADING IN THE GLOBAL ECONOMY— Have Your
Trading Strategies and Profits Kept Pace? . . . . . . . . . . . . . . . . . . 25
The Markets Are Constantly Evolving . . . . . . . . . . . . . . . . . . . 26
The World’s Futures and Equity Markets Are Linked . . . . . . . . 27
Emerging Forces Usher in the New Global Economy. . . . . . . . 29
Market Volatility and Financial Crises Are Here to Stay. . . . . . . 31
Chapter 2
SINGLE-MARKET ANALYSIS—Trading With Tunnel Vision
Can Put You on the Losing Side of a Trade . . . . . . . . . . . . . . . . 35
While Numbers Don’t Lie, They Can Be Deceiving . . . . . . . . . 36
The Goal Is to Forecast Market Trend Direction . . . . . . . . . . . 36
You Can Play the Markets, or You Can Time the Markets . . . . . 37
Technical Analysis Has Not Kept Pace With the Markets. . . . . . 38
Traders Need to Take Off Their Blinders. . . . . . . . . . . . . . . . . 41
Chapter 3
INTERMARKET ANALYSIS—Seizing Trading Opportunities in a
Shrinking World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Intermarket Analysis in the Equity and Commodity Markets . . . 46
No Market Is Exempt From Globalization . . . . . . . . . . . . . . . 49
7
Why Markets Converge or Diverge . . . . . . . . . . . . . . . . . . . . 50
Intermarket Dynamics Must Be Taken Into Consideration . . . . 51
Early Attempts at Intermarket Analysis Fall Short . . . . . . . . . . 51
Tracking Related Markets Pays Off . . . . . . . . . . . . . . . . . . . . 52
Full Field of Vision Is Critical . . . . . . . . . . . . . . . . . . . . . . . . 53
Intermarket Analysis: In the Right Place at the Right Time. . . . 56
The Only Thing Certain Is Uncertainty Itself . . . . . . . . . . . . . 57
Chapter 4
TODAY’S MARKETS HAVE CHANGED—Why Trend Forecasting
Beats Trend Following and How Traders Can Profit. . . . . . . . . . 59
Moving Averages Are Lagging Indicators. . . . . . . . . . . . . . . . . 60
Moving Averages Are Popular —But Something’s Missing. . . . . 62
Moving Average Crossovers Lead to Whipsaws . . . . . . . . . . . . 63
Computing a Simple Moving Average Is Easy . . . . . . . . . . . . . 65
Displaced Moving Averages: Close But “No Cigar” . . . . . . . . . . 66
A New Way to Forecast Moving Averages . . . . . . . . . . . . . . . . 66
Leading Indicators Give You a Competitive Edge. . . . . . . . . . . 69
Chapter 5
VANTAGEPOINT FORECASTS MARKET DIRECTION—
How to Get a Sneak Preview of Where the Markets Are
Going and Use This Information to Your Advantage . . . . . . . . . 71
VantagePoint Monitors Major Financial Markets . . . . . . . . . . . . 71
Five Neural Networks Make Independent Forecasts . . . . . . . . . 73
What VantagePoint’s Daily Report Tells You . . . . . . . . . . . . . . 76
Intermarket Charts Show You What’s Ahead . . . . . . . . . . . . . 80
VantagePoint Is Quick and Easy . . . . . . . . . . . . . . . . . . . . . . 82
How to Find a Good Trade . . . . . . . . . . . . . . . . . . . . . . . . . 83
Here’s How to Get Added Confirmation . . . . . . . . . . . . . . . . 84
Day and Position Trading With Tomorrow’s Price Forecasts . . . 88
Stop Placement Based on Forecasts Not Hunches. . . . . . . . . . 89
Other Markets Give Added Confirmation . . . . . . . . . . . . . . . . 90
How To “Cherry-Pick” the Best Trades to Take. . . . . . . . . . . . 91
8
Chapter 6
NEURAL NETWORKS—How to Raise Your Financial IQ
to Stay Ahead of the Competition . . . . . . . . . . . . . . . . . . . . . . . 93
Neural Networks Combine Technical and Intermarket Data . . . 94
Neural Networks Learn Patterns and Make Forecasts . . . . . . . . 95
Chapter 7
THE NEXT HORIZON—Where Do We Go From Here
and What Does This Mean for Traders? . . . . . . . . . . . . . . . . . . 99
There Will Never Be a Financial Crystal Ball . . . . . . . . . . . . . 101
Trading Resource Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
About the Author and Market Technologies Corporation . . . . . . . . 115
9
Foreword
T
hey say timing is everything. Nowhere is that more true than
in the financial markets. It’s especially timely that Lou
Mendelsohn’s book on intermarket analysis should appear at
the start of the new millennium. At the start of the last decade, I pub-
lished a book on the same topic—Intermarket Technical Analysis:
Trading Strategies for the Global Stock, Bond, Commodity, and Cur-
rency Markets (John Wiley & Sons, 1991). At that time, the principles
of intermarket analysis seemed heretical by suggesting that single-
market analysis (that had been utilized for the past century by mar-
ket technicians) was no longer adequate. By the end of the decade,
those seemingly radical ideas had become so accepted that the
Market Technicians Association listed intermarket analysis as a branch
of technical analysis.
It’s hard, for example, for any market analyst who lived through the
Asian crisis of 1997 to dispute the existence of global linkages —and
the interdependence of all financial markets. The collapse of one
Asian currency in the summer of that year caused a domino effect
throughout all of Asia. Before long, Asian bankers were raising inter-
est rates to stem the spreading currency collapse. That had a devas-
tating effect on the Asian stock markets. That deflationary threat
pushed global commodities into a free-fall and caused a massive rota-
tion out of global stocks into U.S. Treasury bonds.
It’s equally hard to argue with how the tripling of oil prices during
1999 pushed global interest rates higher and caused a bear market in
bonds. That prompted the Federal Reserve Board to start raising inter-
est rates in the middle of that year. A series of Fed tightenings over
the next twelve months had a predictably restraining effect on the
bull market in stocks. The impact of rising oil prices (and rising inter-
est rates) could also be seen in sector rotations within the stock mar-
ket. While rising oil prices were bullish for the energy sector during
Trend Forecasting With Technical Analysis 11
1999, they had a predictably bearish impact on interest-rate sectors of
the stock market (like financial stocks and utilities) and oil-sensitive
groups like the airlines. By the middle of the year 2000, economists
who had ignored the surging oil market during 1999 were crediting
that surge with slowing down the U.S. economy.
In case anyone wasn’t convinced a decade ago, market events
since then have amply demonstrated that all markets are linked—
and that a thorough market analysis has to take these intermarket
relationships into consideration. Lou Mendelsohn’s book takes those
intermarket ideas to an even more practical level. As he correctly
points out, the problem with intermarket relationships is that there
are so many of them. One of his intermarket trading models incor-
porates as many as nine related markets. With so many markets inter-
acting at the same time, it has become increasingly difficult for the
human mind to make sense of it all. Enter neural networks.
One of Mendelsohn’s greatest contributions to intermarket analysis
has been his application of neural networks to the process. He shows
how a neural network can take any number of related factors into
consideration, analyze them, and draw some practical conclusions.
And, those conclusions lead to the real benefit —winning market
trades. The results of two decades of pioneering work has produced
highly successful intermarket trading programs. Since I was the one
who first described these intermarket principles ten years ago, I feel
indebted to Mendelsohn for proving that those ideas do in fact work
and that they can be profitably applied to the financial markets.
Neural networks even incorporate fundamental factors into techni-
cal and intermarket work. When talking about things like inflation
and interest rates, the technical analyst sounds more like an econo-
mist than a chartist. Mendelsohn incorporates intermarket, funda-
mental, and technical considerations into an approach that he calls
“synergistic market analysis” —a term I first heard him use when I
interviewed him on CNBC
™
. For some purists, that may be a prob-
lem. For the rest of us, it’s just another step in the evolution of tech-
nical analysis. Intermarket work has a tendency to blend the funda-
mental and the technical —a trend that I expect to accelerate in the
new millennium. And I suspect that many of the techniques
described by Mendelsohn in this pioneering work will play an impor-
tant role in helping to bring about those changes.
12 Trade Secrets
Mendelsohn warns that what worked for technical analysts in the
old century may not work in the new one. Many of us started out
using pencils and rulers. We graduated to hand-held calculators be-
fore switching over to computers. Now comes neural networks.
Different times demand different tools. An increasingly interdepen-
dent financial marketplace will demand an even better set of tools.
It will also demand a more comprehensive approach to market
analysis that incorporates all geographic regions and all markets —
in other words, an intermarket approach.
—John Murphy
? ? ? ? ? ?
Mr. Murphy is also the author of Technical Analysis of the
Financial Markets and The Visual Investor and is the presi-
dent of MurphyMorris.com.
Trend Forecasting With Technical Analysis 13
Preface
T
his book explores the application of intermarket analysis,
which analyzes the relationships between financial markets
and their influences on each other. It examines the critical role
that intermarket analysis plays in assisting traders to identify and antic-
ipate changes in market direction in today’s globally interconnected
financial markets.
These markets include stock indexes such as the Dow Jones Indus-
trial Average
SM
, London’s FTSE
™
100 Index, the Nasdaq Composite
®
Index, the Nasdaq-100 Index
®
, the Nikkei Stock Average
®
(Japan) and
the Standard & Poor’s 500
™
Stock Index; currencies such as the British
pound, Japanese yen, Swiss franc and the U.S. Dollar Index; energy
markets such as crude oil, gasoline and heating oil; interest rate mar-
kets such as the eurodollar, Treasury bonds and Treasury notes; as
well as individual equities.
As the burgeoning global economy of the 21st century, fostered by
advancements in information technologies, contributes to the further
integration of the financial markets, intermarket analysis will become
an integral part of the overall field of technical analysis. Intermarket
analysis empowers traders to make more effective trading decisions
based upon the linkages between related financial markets. By incor-
porating intermarket analysis into your trading strategies, rather than
limiting your scope of analysis to each individual market, these rela-
tionships and interconnections between markets will work for you
rather than against you.
Suggestions are made for how intermarket analysis can be used in
conjunction with traditional single-market technical indicators to pro-
vide a more comprehensive framework of analysis and broadened
trading perspective. This book also introduces VantagePoint Intermar-
ket Analysis Software which has achieved an astounding accuracy
rate of nearly 80% at forecasting market direction, and offers insights
Trend Forecasting With Technical Analysis 15
16 Trade Secrets
into how day traders and position traders in both the futures and
equity markets can use this powerful analysis tool to improve their
trading performance and achieve a competitive advantage over other
traders.
This book will be of interest to both experienced individual and
professional traders as well as newcomers to the financial markets
who want to create wealth in today’s global markets.
Introduction
A
fter trading stocks and options for nearly a decade using var-
ious technical analysis methods, in the late 1970s, with en-
couragement from a physician friend who traded gold futures,
I started to both day trade and position trade commodities while
working professionally as a hospital administrator.
At first I subscribed to chart services, which had to be updated by
hand during the week. I often joked to my wife about having to
sharpen my #2 lead pencil so often, since the dullness of its point
affected how my support and resistance lines were drawn, which in
turn determined where I placed my stops. This was very annoying to
me whenever I anticipated the market direction correctly only to miss
out on a big move after being stopped out prematurely at a loss due
to an ill-placed stop.
Using a hand-held calculator to compute technical indicators in the
days before microcomputers, I learned the underlying theories and
mathematical equations for various indicators such as moving aver-
ages, and devised mathematical shortcuts to expedite my daily cal-
culations.
I was quite excited when I purchased my first microcomputer in
the late 1970s. Before long I was teaching myself programming and
writing simple software programs to automate many of these calcu-
lations.
I quickly realized that the marriage of microcomputers with tech-
nical analysis would revolutionize financial market analysis. While I
had been hooked on trading and technical analysis since the early
1970s, it was the decision to apply computers to technical analysis
that changed my life.
In 1979, at thirty-one years old, intent on pursuing this goal, I
formed Market Technologies Corporation. A year later, with my wife
Illyce’s support, I left the health-care industry to devote my full atten-
Trend Forecasting With Technical Analysis 17
18 Trade Secrets
tion to commodity trading, technical analysis and trading software de-
velopment.
My intent was to design technical analysis software that would do
more than just automate and speed up calculations I had been doing
by hand each evening with a calculator. I wanted to be able to cre-
ate and back-test various trading strategies to identify and forecast the
market direction of the commodity markets that I traded.
In 1983, I released ProfitTaker, the first commercially available
microcomputer trading software to perform strategy back-testing and
optimization. With its automated back-testing capabilities, ProfitTaker
represented a milestone in the evolution of computerized technical
analysis.
That same year I authored a series of articles in Futures
®
magazine.
In these articles I introduced the concepts of back-testing and opti-
mization for microcomputers and discussed the impact that these
innovations would have on technical analysis and trading.
Throughout the 1980s, I continued to develop more powerful trad-
ing software. I also wrote articles and collaborated on books on trad-
ing, in which I discussed the dangers of curve-fitting and over-opti-
mization in trading strategy back-testing. Additionally, I spoke about
these pitfalls in national television, radio, and magazine interviews
and at financial industry conferences as an invited speaker. Before
long, strategy development and back-testing had attracted the atten-
tion of traders around the world who were purchasing microcom-
puters for the first time.
While there was resistance from a few professionals in the finan-
cial industry whose own software had been rendered obsolete by
back-testing and optimization or who felt threatened by these inno-
vations in computerized technical analysis, I received encouragement
at the time from a number of prominent technicians and traders.
These included Darrell Jobman, who was editor-in-chief of Futures
magazine, as well as Larry Williams and Jake Bernstein, who were
early supporters of mine—and to whom I am grateful.
Several ProfitTaker clients subsequently became software develop-
ers themselves, and promoted competitive software programs emu-
lating ProfitTaker’s back-testing and optimization capabilities. Other
existing software developers, likewise, later introduced their own ver-
sions of back-testing software, including Omega Research’s Trade-
Station
®
in 1991.
Today back-testing and optimization are so integral to single-mar-
ket technical analysis that traders take these capabilities for granted.
I find it somewhat amusing when I hear new traders just learning
about technical analysis tell me that back-testing has always been in
trading software—as if automobiles have always existed.
By the mid-1980s, through my technical research and observations
on the markets, it had become apparent to me that single-market
technical analysis methods would no longer be sufficient. Given the
changes that were occurring in the financial markets due to advance-
ments in computing and telecommunications technologies and the
emerging “global economy,” I realized that such methods which look
internally at only one market at a time (and typically lag behind the
market) were too limited.
In 1986, while searching for a way to broaden the scope of tech-
nical analysis, I developed the first commercially available intermar-
ket analysis software for microcomputers. This program addressed
market interdependencies by using a spreadsheet format to correlate
movements in related markets, as well as expectations of economic
statistics, with the anticipated trend direction of a target market.
The global stock market crash of October 1987 starkly affirmed my
convictions about the interdependencies of the world’s futures, equi-
ty and derivative markets. At that point, I was convinced that inter-
market analysis would become an essential part of technical analysis
as the world economies and financial markets continued to become
more intertwined.
Despite my accomplishments at developing intermarket analysis
software, I was not satisfied with the mathematical tools I had used
to correlate market data from related markets. Then in the late 1980s
after experimenting with an artificial intelligence technology known
as neural networks, I concluded that they were ideally suited to the
tasks of finding repetitive patterns and nonlinear relationships
between a target market and related markets, and accurately fore-
casting market direction of the target market.
In 1991, after considerable research and development involving the
application of neural networks to financial forecasting, I introduced my
most advanced software program—VantagePoint Intermarket Analy-
Trend Forecasting With Technical Analysis 19
20 Trade Secrets
sis Software. VantagePoint uses neural networks to make short-term
forecasts of the market direction and prices of various financial
markets.
Around this same time, other technicians, including John Murphy,
the technical analyst for CNBC, working independently, were also ex-
ploring intermarket relationships, primarily from an intuitive and
descriptive standpoint. Their work lent further credibility among
traders to the new arena of intermarket analysis.
Since the late 1980s, I have written extensively in articles and books
about globalization and the integration of the world’s financial mar-
kets. During this time I have continued my research and software
development involving intermarket analysis, creating powerful trend
forecasting trading strategies built around predicted moving averages.
The technical focus of this book’s presentation is on how inter-
market analysis, through the application of neural networks, can be
used to forecast moving averages, making them a leading rather than
a lagging technical indicator.
• Chapter 1 discusses the globalization of the financial markets and
outlines some of the major factors that are responsible for the
emergence of the global economy.
• Chapter 2 highlights the limitations of traditional technical analy-
sis methods, particularly the emphasis on single-market analysis
and the reliance upon lagging trend-following indicators.
• Chapter 3 examines intermarket analysis as a logical extension of
technical analysis and offers various ways that intermarket analysis
can be used by traders to seize trading opportunities that other
traders miss.
• Chapter 4 explains the strengths and weaknesses of traditional mov-
ing averages, and shows how trend forecasting, by using neural net-
works applied to intermarket data, outperforms trend following.
• Chapter 5 describes VantagePoint’s market forecasting capabilities.
This chapter also presents various market timing trading strategies
utilizing predicted moving averages, which can be used by both
day traders and position traders.
• Chapter 6 looks at the application of neural networks to inter-
market analysis and briefly outlines the basics of neural networks
and how they can benefit traders in today’s global markets.
• Chapter 7 discusses the evolution of financial market analysis in
the first decades of the 21st century. It suggests a comprehensive
approach that I call “synergistic market analysis,” which combines
technical, intermarket and fundamental data into one framework
for the purpose of analysis and forecasting.
In summary, this book discusses the globalization of the world’s
financial markets and the application of intermarket analysis in devel-
oping and implementing powerful trend forecasting and market tim-
ing trading strategies in the equity, options, derivative and futures
markets.
Trend Forecasting With Technical Analysis 21
Trend
Forecasting
With Technical
Analysis
Unleashing the Hidden Power
of Intermarket Analysis
to Beat the Market
TRADING IN THE GLOBAL
ECONOMY
Have Your Trading Strategies
and Profits Kept Pace?
D
uring the last two decades of the 20th century, following the
advent of microcomputers, participation in the financial mar-
kets by individual traders has grown tremendously. Trading
software has proliferated as an increasing number of traders have em-
braced technical analysis methods for making trading decisions.
While microcomputers have become substantially faster and trad-
ing software has likewise undergone significant improvements in
speed, performance and user-friendliness, the overall success rate of
traders from a profitability standpoint has not materially improved.
The reason, in my opinion, is that the single-market emphasis of tech-
nical analysis has not kept pace with structural changes that have oc-
curred in the financial markets related to the emergence of the glob-
al economy.
Now, more than ever before, mass psychology and market senti-
ment seem to change daily, if not hourly, as market direction abrupt-
ly shifts from bullish to bearish and back again. One day a futures
market or individual stock is overbought, the next day it is oversold.
Today’s market darling is tomorrow’s ugly duckling. One day con-
cerns over inflation are of paramount importance to traders, the next
day the subject is practically forgotten as they move on to the next
hot topic. Fears over interest rates and “hard landings” wax and wane
as traders, with the attention span of hyperactive children, have diffi-
culty maintaining their focus, discipline and perspective.
Trend Forecasting With Technical Analysis 25
Chapter 1
26 Trade Secrets
To the novice, these sudden shifts between greed and fear, bull-
ishness and bearishness, optimism and pessimism, hope and resig-
nation, seem to exist in a vacuum without rhyme or reason. Yet pat-
terns of market behavior repeat themselves over and over again. They
can be found within each market, such as the Dow Jones Industrial
Average, at different periods in time, and from an intermarket per-
spective by analyzing relationships between related markets.
Domestic and foreign markets now, more often than not, move in
concert, driven by common financial, political and economic forces
affecting the global economy.
Today’s traders can no longer rely solely upon single-market tech-
nical analysis methods, which were designed for the more indepen-
dent and less volatile domestic markets of the late 20th century.
Clearly, intermarket analysis tools which can identify reoccurring
patterns within individual financial markets and between related
global markets afford traders a broadened trading perspective and
competitive edge in today’s trading environment, which has been
transformed by the mounting globalization and integration of the
world’s financial markets.
The rapidness of change in the global economy and the growing
interdependencies between global futures and equity markets should
make this topic of utmost importance to traders who want their
involvement in the financial markets to be profitable, not just a costly
pastime. Since the markets are a financial version of Darwin’s survival
of the fittest competition, intermarket analysis tools —that build and
expand upon the single-market analysis methods which defined tech-
nical analysis in the late 20th century—demand serious attention.
The Markets Are Constantly Evolving
With the emergence of a new era of global electronic communica-
tions, heralded by the first transatlantic satellite transmission in 1962,
and the subsequent creation of currency, interest rate, oil and stock
index futures in the 1970s and 1980s (following the decision by the
United States to abandon fixed exchange rates in 1971), the world’s
futures and equity markets, previously distinct from one another,
began to coalesce.
The proliferation of financial futures laid the early foundation for
the global integration of the financial markets and for intermarket
analysis to become a necessary component of technical market analy-
sis, as volatility in interest and exchange rates, as well as in oil prices,
created new opportunities and risks for speculators and hedgers,
including multinational corporations.
In the past, trading was conducted on a local level within separate
time zones on individual domestic stock and commodity exchanges.
Now, at the dawn of the 21st century, the melding of the debt, equi-
ty, futures, derivative and options markets throughout the world con-
tinues unabated.
The World’s Futures and Equity Markets Are Linked
Take a look at the chart above (see Figure 1-1). It displays a one-
year (re-scaled) comparison chart of two stock indexes. Notice how
closely they track each other. Try to guess which markets they are.
If you guessed that they are the Nasdaq Composite Index and the
Nasdaq-100 Index, two closely related indexes, you are half right. The
one on the top of the chart is the Nasdaq Composite Index. However,
the one on the bottom is not even a U.S. market. It is a Latin American
Index created by Morgan Stanley Dean Witter to track growth stocks
in Argentina, Brazil, Chile, Columbia, Mexico, Peru and Venezuela.
Trend Forecasting With Technical Analysis 27
Figure 1-1. STOCK INDEXES MIRROR EACH OTHER
Through intermarket linkages, related markets alert traders to impending trend
changes.
Source: www.bigcharts.com
28 Trade Secrets
This chart illustrates the fact that even linkages between seemingly
unrelated markets cannot be ignored by traders as the globalization
of the financial markets continues to evolve.
Already the New York Stock Exchange
®
, the Nasdaq
®
and the Chi-
cago Board of Trade, each mindful of the trend toward market glob-
alization, have begun to build strategic alliances with foreign ex-
changes.
In the year 2000, the New York Stock Exchange announced its
“Global Equity Market
™
” platform, which will involve alliances with
various foreign exchanges, such as the Tokyo Stock Exchange, Paris-
Bourse, Toronto Stock Exchange, Amsterdam Stock Exchange, Stock
Exchange of Hong Kong, Australian Stock Exchange, Brazil’s Bovespa,
Brussels Stock Exchange and Mexico’s Bolsa.
At the same time the Nasdaq, through
alliances with the Australian and Hong
Kong exchanges, the Osaka Securities
Exchange involving the creation of
“Nasdaq Japan
SM
,” the Deutsche Boerse
and the London Stock Exchange in
Europe, and other possible alliances in
Canada and Latin America, is pursuing
its own strategic plan for participation
in the emerging 24-hour global financial
marketplace.
Similarly, the world’s two largest futures exchanges, the Chicago
Board of Trade and Frankfurt’s Eurex exchange, have teamed up to
launch a joint electronic trading platform beginning in the year 2000.
Eventually alliances such as these will allow traders to trade any
financial instrument, anywhere in the world, at any time over seam-
less, electronic global trading platforms.
Having lived through the dismantling of the Berlin Wall, the reuni-
fication of Germany, the breakup of the U.S.S.R. and the end of the
Cold War in the closing years of the last century, it would not surprise
me at all if the New York Stock Exchange and the Nasdaq, for
instance, were to announce the joint creation of a totally compre-
hensive electronic global trading network, in partnership with major
stock and commodity exchanges throughout the world. Necessity is,
after all, the mother of invention.
Linkages between
seemingly unrelated
markets cannot be
ignored by traders
as the globalization
of the financial
markets continues
to evolve.
Before long, trading in the financial markets will be conducted day
and night electronically, in the virtual world of cyberspace far from
the brick and mortar trading floors of today’s stock and futures
exchanges. I can easily envision today’s concepts of “after hours trad-
ing,” “extended trading” and even “open outcry” becoming historical
footnotes to our lexicon, just as the “buggy whip” and the “horseless
carriage” were relegated at the dawn of the 20th century.
With the implementation of twenty-four-hours-a-day trading involv-
ing literally thousands of financial instruments, including esoteric
ones not yet conceived, even small institutional trading organizations
will need to staff their trading operations around the clock. Many
individual traders, however, will suffer from market-induced insom-
nia, as they feel compelled to check on their market positions at all
hours of the night, fearing some external cataclysmic event that trig-
gers an abrupt change in trend direction, or worse yet an overnight
worldwide meltdown of the financial markets.
High-flying Internet, technology and biotechnology stocks are
already traded like commodities by electronic day traders. This stands
to reason, since an uptrend is an uptrend, a trend reversal is a trend
reversal and patterns repeat themselves, regardless of the label that is
put on each market. It doesn’t matter if it’s pork bellies, orange juice,
sugar, Treasury notes, the S&P 500
®
Index, the Swiss franc, crude oil,
Intel or Amgen.
As stock index futures proliferate, index trading expands, Internet
chat rooms continue to bustle with traders sharing trading tips, elec-
tronic day trading becomes recognized as a legitimate “occupation,”
mutual funds trade intra-day, and futures contracts on individual
stocks make their debut, this worldwide intermingling of equities and
futures will accelerate.
Emerging Forces Usher in the New Global Economy
Below is a brief account of some of the more significant techno-
logical, economic, financial and political forces that are converging to
bring about the globalization of the world’s financial markets in the
21st century:
• Advancements in information technologies including microcompu-
ters, satellite, software and telecommunications, which are being
focused on the global expansion and commercialization of the
Trend Forecasting With Technical Analysis 29
30 Trade Secrets
Internet and the development of electronic global communications
and trading networks. Transactions involving the purchase and
sale of financial instruments, tangible property and the raising of
capital will be conducted freely, instantaneously and competitive-
ly on a worldwide level. These developments will render obsolete
the concepts of local financial markets and economic nationalism.
• The expansion of global derivatives trading involving interest rate
futures, stock indexes and options, and the marriage of derivatives
trading with information technologies will continue to meld previ-
ously disparate markets, further increasing market interdependen-
cies and bringing about the total internationalization of the finan-
cial markets.
• Increased global free trade and competition, and the globalization
of multinational corporate financing strategies involving capital
formation, hedging of foreign exchange and interest rate risk,
cross-border listing of shares on multiple exchanges in different
countries, corporate consolidations and cooperative competition
through global alliances, and mergers and acquisitions (particular-
ly within brokerage, investment banking and telecommunications,
as well as between exchanges) across national boundaries.
• Government deregulation involving the banking, brokerage, ener-
gy, telecommunications and transportation industries. Reductions in
marginal tax rates which stimulate economic activity and global
competition, reallocation of capital geographically and from the
public to the private sector, increased productivity, lowered costs,
and spurred innovation in the development of new technologies.
• Productivity gains brought about by advancements in information
technologies positively affecting the cost structure of corporate
enterprises, streamlining and shortening supply chains and cus-
tomer channels.
• Demographic increases in demand for financial assets and broader
participation in privatized, tax-deferred profit sharing and retire-
ment plans by baby boomers.
• The emergence of democratically elected governments, increased
personal rights, free enterprise, private ownership, the privatization
of formerly state-owned enterprises, the encouragement of the spir-
it of entrepreneurship, and the adoption of market-based econom-
ics in developing countries throughout the world, as well as the
expansion of free trade with China and its likely inclusion in the
World Trade Organization.
Market Volatility and Financial Crises
Are Here to Stay
All of these factors, as well as others, have ushered in a new era in
which there will eventually be just one globally integrated network
of financial markets into which all futures, equity and derivative mar-
kets fit as interdependent parts —like pieces in a giant jigsaw puzzle.
If you pick up a financial magazine or
newspaper, or listen to financial news
programs, you’ll hear commentators,
money managers, corporate executives,
financial analysts and economists talk
about a shift in the economic paradigm
referred to as the “new economy” or
“global economy.” This is an emerging
economic world order driven by global
voice, data and video telecommunica-
tions, wireless m-commerce, worldwide
e-commerce and an emerging electron-
ic global financial network encompass-
ing previously independent financial
markets.
Already, when news of an unexpect-
ed change in a government-reported
economic statistic is released, terrorism
occurs in the Mideast, the U.S. Federal Reserve Board or European
Central Bank announces a change in interest rates, or an Asian coun-
try devalues its currency, this news is beamed around the world
instantly by satellite on CNN
™
, CNBC and over the Internet.
Within seconds billions of dollars in financial assets can be con-
verted and redeployed anywhere around the world electronically at
the touch of a mouse button by a large institutional trader without
regard to national, political, social or economic consequences, geo-
graphical considerations, or time of day. A well-placed rumor or fic-
titious press release, perhaps instigated by a new breed of global
Trend Forecasting With Technical Analysis 31
This is an emerg-
ing economic world
order driven by
global voice, data
and video telecom-
munications, wire-
less m-commerce,
worldwide e-com-
merce and an
emerging electronic
global financial
network encom-
passing previously
independent fi-
nancial markets.
32 Trade Secrets
cyber-saboteur, can now set off an explosion of events globally with
instantaneous and potentially harmful financial ramifications, even if
the false information is subsequently proven to be unfounded.
The first instance of the financial market equivalent of an earth-
quake of global proportions occurred on October 19, 1987, as the
world’s futures and equity markets cascaded downward like domi-
noes falling against each other. Once the first domino falls, it precip-
itates a chain reaction that reverberates throughout the world (see
Figure 1-2).
Fortunately, catastrophic damage to the world’s financial markets
and economies was averted in 1987, and during aftershocks from less
powerful earthquakes on the financial Richter scale in the late 1990s.
Yet these events set the stage for what will undoubtedly dot the world
financial landscape in the 21st century, even under the most opti-
mistic global economic scenarios.
As advancements in telecommunications and information tech-
nologies accelerate, time-sensitive global market information be-
comes more widely available over the Internet, and electronic day
trading of stocks, futures, and even mutual funds becomes wide-
spread, uncharted levels of intra-day and inter-day market volatility
may become commonplace in the first decades of the 21st century.
Suffice it to say that “normal” market sell-offs and corrections, some
Figure 1-2. GLOBAL MARKETS REACT TO THE DOMINO EFFECT
Financial crises can spin out of control quickly, as interdependent financial markets
fall, setting off a chain reaction that reverberates worldwide.
Source: Market Technologies Corporation
abrupt and short lived, others protracted, but all very painful and
costly to the unwary, have not been swept under the rug by the new
economic paradigm.
To date, crisis control by the various sectors of the world’s financial
markets including stock and futures exchanges, central banks, clear-
ing organizations, finance ministries, regulatory organizations and in-
ternational banking institutions still apparently operates on an ad hoc
basis. Presently, it is unclear whether or not the existence of a highly
interdependent global communications and trading network, toward
which the world’s financial markets are heading, will mitigate or exac-
erbate global financial crises in the future.
In this climate, the difference between
the financial “haves” and the “have nots”
will be determined by which traders
have access to the most robust inter-
market analysis tools and information
necessary to act decisively, particularly
at the onset of instability in the financial
markets.
This is especially critical for the mil-
lions of baby boomers in the United
States, Europe, Japan and elsewhere,
desperately in need of building and
protecting their wealth to carry them
through their retirement years (poten-
tially lengthened by extended life
expectancies due to breakthroughs in
biotechnology).
With after-tax rates of return on bank deposits and money market
funds barely keeping pace with inflation, and anemic returns on hard
assets such as gold, the only place these baby boomers can turn to
for growth potential and liquidity is the global futures and equity
markets.
These realizations are what prompted me in the mid-1980s to
focus my attention on the broader framework of intermarket analy-
sis, and to develop VantagePoint as an intermarket-based market
forecasting tool. VantagePoint forecasts short-term trends and prices
based upon the pattern recognition capabilities of neural networks.
Trend Forecasting With Technical Analysis 33
Presently, it is
unclear whether or
not the existence of
a highly interdepen-
dent global commu-
nications and
trading network,
toward which the
world’s financial
markets are head-
ing, will mitigate or
exacerbate global
financial crises in
the future.
34 Trade Secrets
It answers these four important questions every trader must grapple
with each day:
• Which direction is the market heading?
• How strong will the move be?
• When will the current trend lose strength, make a top or bottom
and reverse direction?
• What will tomorrow’s trading range be?
In Chapter 5, I will show you how VantagePoint tackles these is-
sues. First, I want to discuss single-market technical analysis and then
compare it with intermarket analysis so you can gain a better under-
standing of how intermarket analysis can dramatically improve your
trading performance.
SINGLE-MARKET
ANALYSIS
Trading With Tunnel Vision
Can Put You on the
Losing Side of a Trade
A
nalysis of the behavior of financial markets for the purpose of
identifying and forecasting market direction has historically
and traditionally been divided into two distinct schools: fun-
damental analysis and technical analysis.
The rationale of fundamental analysis is to make trading decisions
by forecasting market direction based upon underlying economic fac-
tors affecting a particular stock or futures market. For example, a trad-
er sells futures contracts on U.S. Treasury notes anticipating a price
decline due to expected increases in interest rates by the U.S. Federal
Reserve Board; buys corn or soybean contracts based on estimates of
crop damage due to expected drought conditions; or buys shares of
Intel or Oracle on expectations that they will beat the Street’s quar-
terly earnings estimates.
The premise behind technical analysis is that all of the internal and
external factors that affect a market at any given point in time are
already factored into that market’s price. In other words, a market’s
current price is thought to reflect the rational collective judgment of
all market participants, each with his own information pertaining to
that market and perception of what he anticipates the market direc-
tion is likely to be in the near future.
Trend Forecasting With Technical Analysis 35
Chapter 2
36 Trade Secrets
While Numbers Don’t Lie, They Can Be Deceiving
With the assumption that the current price fully discounts all of the
available information about a market and the influences or forces
affecting it, technical analysis, in contrast with fundamental analysis,
does not delve into any of the underlying economic factors that influ-
ence the market.
Instead, technical analysis uses various technical studies, indicators
and market-forecasting theories to analyze market behavior. Historical
market data such as price, volume and open interest of commodity
contracts is examined to identify repetitive patterns, which, if found,
can be used to determine the current market trend, anticipate future
market direction, and provide price targets for entry and exit loca-
tions. This analytic process is depicted in Figure 2-1.
The Goal Is to Forecast Market Trend Direction
While fundamental analysis and technical analysis each have their
own underlying philosophical foundation and specific analytic meth-
odologies that look at the markets from two distinct standpoints, both
methods have the same goal: to identify and forecast the market trend
direction of various financial markets. These include:
• Individual equities, such as Cisco Systems, Intel and Amgen.
• Stock indexes, such as the Nasdaq-100 Index, S&P 500 Index and
Nikkei
®
.
Figure 2-1. TECHNICAL ANALYSIS IS AN ANALYTIC PROCESS
Traders analyze past market data to find repetitive patterns which are used to deter-
mine the market trend and forecast where it’s going next.
Source: Market Technologies Corporation
Technical
Studies,
Indicators
and Theories
Market
Data
Repetitive
Price
Patterns
Goal
Identify Current Trend
Forecast Future Trend
and Prices
Estimate Price Targets
• Interest rates, such as 10-year U.S. Treasury notes, 5-year U.S.
Treasury notes and eurodollar.
• Currencies, such as the U.S. Dollar Index, Swiss franc and British
pound.
• Energies, such as crude oil, heating oil and gasoline.
• Metals, such as gold, silver and platinum.
Through either fundamental or technical analysis, traders attempt
to form expectations about the trend direction of each market, and
make trading decisions with the hope of realizing a profit if their mar-
ket forecasts prove to be correct.
The underlying assumption made by fundamentalists and techni-
cians is that their methods result in superior trading performance.
This has been a controversial subject over the years, with counter-
vailing arguments that the practices of both fundamental and techni-
cal analysis are futile efforts.
From my experience over several decades as a trader and techni-
cal analyst, I am convinced that being able to make a reasonably
accurate short-term trend forecast of market direction improves the
outcome of the decision-making process —resulting in more prof-
itable trading. However, even if a trader were able to make a perfectly
accurate forecast of market direction, he would still have one final
challenge to surmount. This involves market timing.
You Can Play the Markets, or
You Can Time the Markets
Once a trader analyzes a specific market and forms an opinion
about the likely trend direction of that market, he must still decide
when to get into or out of a position and at what price.
In all walks of life, timing is everything. In the financial markets, if
you forecast the trend direction correctly but your timing is off (by
just one day or even an hour or less) you can still end up losing
money.
Historically, market timing has been particularly challenging for
traders in the futures markets, due to their price volatility, low margin
requirements and high degree of leverage. As the new breed of elec-
tronic day traders moves into and out of high-flying tech stocks with
Trend Forecasting With Technical Analysis 37
38 Trade Secrets
the same speed and indifference that futures traders buy and sell con-
tracts on the Japanese yen or crude oil, more equity traders now con-
cern themselves with market timing than ever before.
As a trader there is nothing more frustrating than to anticipate the
trend direction correctly, get into a position slightly too soon, have
the market go against you, get stopped out, and then have the mar-
ket turn around and move in the direction that you expected. When
this happens, you end up either sitting on the sidelines after taking a
loss, or trying to chase after the market. Identifying the current trend
direction, while important, is not enough. You must also be able to
anticipate when the market is poised to make a top or bottom and
change direction.
Once you can forecast the trend direction, can identify turning
points, and have an expectation of the next day’s price range to help
you determine entry and exit locations, there’s really nothing more in
the way of analysis necessary. Now it’s just a matter of “pulling the
trigger.”
Technical Analysis Has Not Kept Pace
With the Markets
If you read any recent issues of popular financial magazines you’ll
find numerous articles on technical analysis with current price charts
and hypothetical track records, nearly identical in content to articles
published in the financial press ten, twenty, and even thirty years ago!
These updated articles are undoubtedly enlightening to novice trad-
ers just beginning to learn about technical analysis and the financial
markets. Remember how excited you were when you first learned
how to spell “Exponential,” “Fibonacci,” and “Stochastic” and under-
stood what they meant? I cannot begin to count how many dozens
of articles and books on technical analysis I have read over the past
several decades rehashing, for instance, the differences between var-
ious types of moving averages and comparing their effectiveness at
reducing the “lag effect.”
This subject was covered in detail in Perry Kaufman’s Commodity
Trading Systems and Methods originally published in 1978, and in
Charles Patel’s Technical Trading Systems for Commodities and Stocks
published in 1980—to name just two classics in my personal library.
The list could go on and on.
There is a typical path that new traders seem to follow. First, they
learn the ABCs of technical analysis by reading a few introductory
books or magazine articles, or watching educational videos or CDs.
These traders learn about price formations and chart patterns such as
head-and-shoulders, flags, islands, pennants, triangles, support and
resistance trend lines, gap patterns and price channels. Then the
traders might attend free trading seminars in their hometowns spon-
sored by an e-brokerage firm or software vendor and learn about
other technical indicators like candlesticks or moving averages.
Eventually new traders buy mass-mar-
keted trading software programs that
automate the calculations of various sin-
gle-market indicators. After developing
and testing different trading strategies
built around some of these concepts,
such as moving average crossover ap-
proaches, many traders begin thinking
that they are on the verge of getting rich,
and will soon be able to quit their day
jobs and become full-time electronic
day traders. This cruel fallacy has been
perpetuated by alluring promotional ad-
vertisements in the financial industry for
as long as I can remember.
Many of today’s traders have little, if any, personal knowledge of
prior stock market routs, including the 1987 crash, not to mention the
torturous decline of 1974. Just ask any veteran traders like myself
about their trading experiences during the stock market debacle of
1974, when the Dow Jones Industrial Average dropped nearly 50%
from its previous high, and you’ll get an earful. That’s when I learned
the painful lesson about the psychological struggle between greed
and fear, with the latter ultimately demonstrating its more powerful
grip on the human psyche.
Protracted bull markets encourage novices to overestimate their
skills as technicians and traders. Greed seduces traders into forming
unrealistic expectations of annual market returns and the risks inher-
ent in trading. Under such conditions traders develop a false sense of
Trend Forecasting With Technical Analysis 39
Identifying the
current trend
direction, while
important, is not
enough. You must
also be able to
anticipate when
the market is
poised to make a
top or bottom and
change direction.
40 Trade Secrets
self-confidence. They begin to expect quick results, like finding the
Holy Grail trading system and achieving overnight riches without
having to work for it. If it were that easy, every trader would be a self-
made millionaire.
Too often new traders assume that heavily promoted or inexpen-
sive trading tools must be the ones to use, since after all so many
other traders are already using them. Unfortunately, technical analy-
sis tools are not like VCRs, where the most popular ones are usually
the best.
If the masses of traders look at the markets from the same narrow
single-market perspective and lose money doing so, then if you like-
wise limit the scope of your analysis,
common sense would tell you that you
should also expect to lose your money.
This doesn’t take a Ph.D. degree in
applied mathematics to figure out. It’s
just high-school math: if A=B and B=C,
then A=C. Yet too many newcomers to
the markets start off on this losing path
and stay on it until their trading capital
is depleted.
It is foolish to think that at first you
can get by using inexpensive single-
market analysis tools to build up your
trading account until you can afford to
get the right tools. If your spouse devel-
ops a life-threatening heart condition,
you wouldn’t pick a cardiologist based
on how cheap his fees are, with the in-
tention that if the condition improves a little you’ll switch to a more
capable doctor.
Traders are bombarded with a barrage of market information from
a myriad of sources including financial television channels, high-traf-
fic financial websites and Internet chat rooms. While this explosion
of information allows traders unprecedented access to the research
and opinions of many reputable technical analysts, advisors and
money managers, it also exposes traders to the increasingly slick and
deceptive use of misinformation and “disinformation” by charlatans
posing as market gurus in cyberspace.
To succeed in the
financial markets,
you cannot treat
your trading lightly,
as if it’s a hobby.
You must treat it
like a business
and that means you
will need to spend
time and money to
succeed. Do your
homework and
get the best analy-
sis tools from the
get-go.
The pervasiveness of, and ease of access to, all this information
makes today’s generation of traders prone to herd behavior. This herd
mentality results in a psychological phenomenon referred to as
“thought contagion,” which contributes to industry loss statistics.
In the case of futures traders, for instance, it is reported that
upwards of 95% lose their money. If the commercial airline industry
had a comparable fatality record, no one in their right mind would
fly, and Amtrak
®
would be hailed as the safest, most convenient way
to travel cross-country.
To succeed in the financial markets, you cannot treat your trading
lightly, as if it’s a hobby. You must treat it like a business and that
means you will need to spend time and money to succeed. Do your
homework and get the best analysis tools from the get-go, or don’t
bother trading and take a trip to Las Vegas instead. You’ll have a lot
more fun and a lot less aggravation.
Traders Need to Take Off Their Blinders
While even novice traders readily admit that the world’s financial
markets are interconnected, and acknowledge intermarket dynamics
as important factors in determining the trend direction of individual
markets, an overwhelming percentage of traders, particularly those
new to the futures and equity markets in the last few years and espe-
cially those with limited capital, are still either unfamiliar with inter-
market analysis or just don’t know how to incorporate it into their
trading.
These traders hear and read every day about how the markets are
interconnected and affect each other —but don’t really know how to
make the connection themselves. So, like ostriches with their heads
in the sand, they stick with single-market analysis methods and lag-
ging indicators, until it’s too late.
They continue to wear restrictive technical analysis blinders, con-
tent to focus their attention on only one market at a time, as though
each market trades in total isolation. This results in an incomplete
perception of what is really happening—and more importantly what
is about to happen—in the markets that they are trading.
No wonder so many traders run for cover like scared rabbits when
the markets get choppy or there is a sudden trend reversal. If this is
Trend Forecasting With Technical Analysis 41
42 Trade Secrets
how you are currently performing your analysis, you are making your
trading decisions in an intermarket “vacuum.” This can only lead to
failure. If you have a relatively small account to work with, your sit-
uation is even more precarious because you have little margin of
error before your capital is exhausted.
The Blind Men and the Elephant
The “Six Blind Men and the Elephant” parable reminds me of the
limitations of single-market analysis. Each of the men touched one
part of an object that they had discovered in hopes of determining
what it was. Here’s how they each described what they had found:
The first blind man insisted it was some
type of spear. It was sharp, hard, coarse,
and sturdy.
The second blind man concluded it was
some type of rope or whip.
The third blind man thought it was some
type of a wall, since it had a rough tex-
ture and was very firm.
The fourth blind man decided that they
had found some type of an animal, proba-
bly a large snake, since it was long, easy
to bend and had a strange texture.
The fifth blind man thought that they
had found some type of plant. It felt like a
large leaf because of its texture and size.
The sixth blind man was convinced
that they had found a log or branch of
a tree, since he had already heard from
one of the other men that the object felt
like a leaf.
They were all wrong. They had
each only touched a small part of
an elephant and formed incorrect
conclusions based on their limited
observations. The financial mar-
kets are no different. If this had
been a trade, it would have been
a losing one! While an analysis of
each individual market is still
important, it is no longer sufficient
because it fails to take into con-
sideration the whole picture.
As the global integration of the financial markets continues to
extend throughout the financial industry, traders who limit their
analysis to a single market’s past prices (or rely exclusively upon sub-
jective chart pattern analysis or linear forecasting methods such as
trend lines) for clues regarding a market’s future trend direction, will
be at a severe competitive disadvantage. These traders will undoubt-
edly end up watching their trading accounts dwindle, while informed
traders who incorporate intermarket analysis into their trading strate-
gies will be in a position to amass substantial wealth.
In the next chapter, I will discuss intermarket analysis in more
detail, and show how your trading can profit from it.
Trend Forecasting With Technical Analysis 43
INTERMARKET ANALYSIS
Seizing Trading Opportunities
in a Shrinking World
O
ver the past few decades, when the financial markets were
less volatile and tended to trade independently of one
another, single-market methods of analysis were the main-
stay of technical analysis and rightfully so. However, at this juncture,
a narrow characterization of the markets, with its focus (if not preoc-
cupation) on the inward analysis of each individual market, is much
too limited. Traders need to expand their perspective to take into
consideration external factors that affect each market.
Here’s a simple analogy. Imagine yourself as a licensed pilot pre-
paring to fly your private plane from New York City to Washington,
D.C., just before dusk one summer evening. Everything on your pre-
flight checklist indicates that all of the plane’s internal operating sys-
tems are functioning properly, including visual fuel and oil checks,
control movements, altimeter, compasses, flaps, mags and engine
runup. However, you neglect to inquire about one critical external
factor: the flight service in-route weather briefing.
In effect, by ignoring the external environmental context in which
your plane will be flying, you are implicitly assuming that either the
weather conditions will be favorable, or will not adversely affect your
flight. This could make for a “hard landing” (no pun intended) if in
fact the weather conditions prove unfavorable for such a flight.
Is trading Treasury notes, crude oil, the Nasdaq-100 Index or the
Japanese yen any different if you are ignoring the broader intermar-
ket forces affecting these individual markets?
Trend Forecasting With Technical Analysis 45
Chapter 3
46 Trade Secrets
The cliché “what you don’t know can’t hurt you” is false. Ignorance
is not bliss when it comes to piloting planes or trading futures or equi-
ties. If you have the right tools, which give you pertinent information,
you will be able to make calculated decisions; if you don’t, you are
just gambling, either with your life or with your hard-earned money.
Sure, it is worthwhile to analyze the behavior of each individual
market. I still do a lot of that in my trading. Failed double tops, bro-
ken trend lines and prices cutting above or below their 50-day or 200-
day moving average are still useful indicators of market direction, if
for no other reason than the fact that they are followed by so many
traders and acted upon through mass psychology. However, it is not
good enough to look only at each individual market by itself.
Popular single-market technical analysis indicators such as moving
averages and chart pattern formations are lagging indicators which
look retrospectively at an individual market’s past data in an effort to
identify reoccurring patterns which can then be extrapolated into the
future. This type of analysis really boils down to looking at where the
market has been, and trying to guess where it is going.
Since the objective of technical analysis is trend identification and
forecasting, it would stand to reason that this goal could best be
achieved by working with leading indicators that anticipate changes
in trend direction.
I prefer to forecast market direction prospectively in a manner that
captures the character and nature of today’s interdependent financial
markets. This can be accomplished by using intermarket analysis tools
comprised of leading indicators that forewarn whether an existing
trend is likely to continue or is about to change direction. This takes
the guesswork out of trading.
Intermarket Analysis in the Equity
and Commodity Markets
Intermarket analysis had its genesis in both the equity and com-
modity markets. Traditional technical analysis within the equity mar-
kets has historically looked at relationships among individual stocks,
sectors and broad market indexes.
Additionally, comparisons between the debt and equity markets
have been made, as the effects of fluctuating interest rates, inflation-
FIGURE 3-1. DEBT AND EQUITY MARKETS AFFECT EACH OTHER
Comparison chart examines the price relationship between 10-year Treasury notes
and the S&P 500 Index.
Source: VantagePoint Intermarket Analysis Software
ary expectations, and central bank policies have played an increas-
ingly important role in determining the market direction of equities.
More recently, comparisons between broad market indexes repre-
senting various stock markets around the world have been made.
Intermarket analysis within the equity markets include the follow-
ing comparisons:
• Domestic broad market indexes to one another.
• Market sectors to the broad market indexes.
• Individual stocks to broad market indexes.
• Individual stocks to one another within a sector.
• The relationship of price, time and volume to one another.
• The advance/decline line compared to the performance of broad
market indexes.
• Movements in interest rates to movements in stock indexes such as
the relationship between 10-year Treasury notes and the S&P 500
Index, as shown in Figure 3-1.
Trend Forecasting With Technical Analysis 47
10-year Treasury notes
S&P 500 Index
48 Trade Secrets
Figure 3-2. STOCK INDEXES IN DIFFERENT COUNTRIES AFFECT EACH OTHER
Comparison chart examines the price relationship between the Nikkei in Japan and
the Dow Jones Industrial Average in the U.S.
Source: VantagePoint Intermarket Analysis Software
• Stock indexes, such as the Nikkei 225 and FTSE 100, are compared
to similar market indexes in other countries such as U.S. stock
indexes including The Dow
SM
or Nasdaq.
Figure 3-2 depicts a comparison chart of the Nikkei and the Dow
Jones Industrial Average, showing how these two global markets
behave relative to one another.
By their nature, the commodity markets have historically lent them-
selves to intermarket analysis. With both a cash market and numer-
ous futures contract months existing simultaneously on a given com-
modity, and with such closely related commodity complexes as the
grains, meats, currencies, interest rates, stock indexes, metals and
energies, intra-commodity and inter-commodity spread analysis has
been an integral part of technical analysis of the commodity markets
for decades.
Spreads between futures markets of related instruments are looked
at to gain additional insight into market direction. These include:
• The “NOB” (Notes Over Bonds) spread between 10-year Treasury
notes and 30-year Treasury bonds.
Dow Jones
Industrial Average
Nikkei
Trend Forecasting With Technical Analysis 49
• The “TED” (Tbills-Eurodollar) spread between 90-day Treasury bills
and the 90-day eurodollar.
• Spreads between bonds and the Bridge/CRB
®
Futures Price Index,
the U.S. Dollar Index, gold and crude oil, to name a few.
Intermarket comparisons between futures and the equity markets
highlight short-term confirmation or divergence, which provides in-
sight into impending changes in market trend direction. Futures can
be monitored as an early barometer of the equity markets. Futures on
the S&P 500 Index, Treasury bonds and notes, as well as other finan-
cial futures markets including crude oil, the Bridge/CRB Futures Price
Index and the U.S. Dollar Index are increasingly looked upon as hav-
ing strong influences on the equity markets.
For instance, higher Bridge/CRB Futures Price Index prices, sug-
gesting higher inflation down the road for various commodities, tend
to drive Treasury notes prices lower (and interest rates higher) which
is also negative for those sectors of the equity markets linked to these
commodities including the agricultural, banking, energy, metals and
industrials sectors.
Globally related markets can be analyzed with regard to their con-
firmation or divergence from one another over time, in response to
various global and domestic economic considerations. For instance,
changes in interest rates (effected by the U.S. Federal Reserve Board,
European Central Bank or the Bank of Japan), currency devaluations
or sudden spikes in crude oil prices have a pronounced effect on fu-
tures and equity markets worldwide.
Intermarket analysis between like debt instruments in different
countries also offers worthwhile cues concerning future global trends
in interest rates. For example, spreads involving government notes
and bonds from various countries can be examined with respect to
each other, as global arbitrage of interest rates tends to keep interna-
tional debt markets synchronized.
No Market Is Exempt From Globalization
Every market, both domestically and internationally, now appears
to have some effect on every other market, however seemingly dis-
tant and unrelated. A thorough analysis of the outlook of any one
market is now incomplete without looking at it within an intermarket
context.
50 Trade Secrets
Figure 3-3 shows nine related markets that are examined by
VantagePoint’s 10-year Treasury notes program. As the software con-
tinues to be refined as part of my firm’s ongoing research effort to
increase VantagePoint’s predictive accuracy, related markets will
change and more will be added.
Why Markets Converge or Diverge
Although there are direct and inverse relationships that on the sur-
face appear to link markets to one another when they are examined
two at a time, these linkages are neither fixed nor linear in nature.
Instead they are dynamic, and have varying strengths, as well as vary-
ing leads and lags to one another that shift over time.
With the increased emphasis today on on-line day trading (where
twenty minutes is considered long term) novice traders expect the
effects on a market from related markets to be instantaneous. Traders
think that all they have to do is look at what Treasury bonds or notes
are doing at any moment in time to get cues on what the stock mar-
ket will do next. However, this is not how the financial markets work.
Sometimes the order of cause and effect is reversed, with stocks
seeming to lead bonds and notes while at other times the Treasurys
appear to lead stocks. Like the chicken and egg dilemma, it is very
hard to discern which comes first.
Figure 3-3. FINANCIAL MARKETS ARE ALL CONNECTED
Nine related markets are examined by VantagePoint’s 10-year Treasury notes pro-
gram to find hidden patterns and relationships.
Source: Market Technologies Corporation
Eurodollar
U.S. Dollar Index
S&P 500 Index
T-Bonds Swiss Franc
NY Light Crude Oil
Comex Gold
Bridge/CRB Index 5-Year T-Notes
10-Year Treasury Notes
Trend Forecasting With Technical Analysis 51
Intermarket Dynamics Must Be Taken
Into Consideration
Traders are still too preoccupied with the inward analysis of each
market, ignoring the interdependencies of the financial markets and
their effects on one another, which have become more pronounced
as the markets have become increasingly globalized.
Additionally, scant progress has been made at objectively (quanti-
tatively) rather than subjectively (qualitatively) identifying repetitive
patterns in market data, necessary to perform effective forecasting.
Now it is imperative for traders to adopt an intermarket perspective
and incorporate intermarket analysis into their trading strategies, in
order to deal with the global financial markets as they really exist.
If you look at the planet Saturn through an inexpensive, low-pow-
ered telescope, you won’t see the rings that surround it. They are
there, but the tool you are using doesn’t have the capability to dis-
cern them. The same is true for how you look at the markets. While
the interconnections are there, you may not see them—but other
traders do.
Failing to factor into their trading strategies the linkages between
related markets, many traders remain oblivious to the underlying
intermarket forces or market synergy that increasingly affects price
movements in today’s global markets. Unquestionably, this narrow
analytic perspective contributes to the financial fatality rate, among
both experienced and novice traders.
I think it is absurd when I hear traders say that having an accurate
short-term forecast of market direction would be of no benefit to
them in their trading. These traders obviously do not understand the
basic purpose of technical analysis. They have become so caught up
with back-testing number crunching on each individual market that
they have lost sight of the forest for the trees.
Early Attempts at Intermarket Analysis Fall Short
Due to the complexity of the dynamic interactions between finan-
cial markets, it is difficult for the average trader to perform even rudi-
mentary intermarket analysis. Nevertheless, technical analysts have
devised various ways to do so. Here are some popular, yet in my
52 Trade Secrets
opinion somewhat ineffective, ways that analysts and traders attempt
to quantify the effects of related markets:
• Price charts on two markets are compared to one another, and the
difference between the two markets’ prices on a minute-by-minute,
hourly, daily, weekly, or monthly basis is calculated and presented
graphically or numerically, as an indication of future market direc-
tion.
• A ratio of the prices representing two markets is calculated and pre-
sented graphically or numerically to show how the two markets
have behaved relative to one another in the past, to help anticipate
what they are likely to do in the future.
• A statistical linear correlation analysis on two markets is performed.
This approach measures the degree to which the prices of one
market move in relation to the prices of the second market. The
mathematical indicator used to measure correlation is known as a
statistical correlation coefficient.
Tracking Related Markets Pays Off
As the number of markets to be explored from an intermarket per-
spective increases, the effectiveness of using any of the previously
mentioned methods rapidly diminishes. These methods of analyzing
intermarket relationships are limited to price comparisons of only two
markets at a time, often assuming incorrectly that the effects of one
market on another occur without any leads or lags. In addition, such
methods presuppose the effects are linear in nature in a sort of one-
to-one causal relationship. This, too, is not realistic with respect to
how the global financial markets function.
Leads and lags exist between domestic and international econom-
ic activity and the financial markets, and between related domestic
and global financial markets. Sometimes the effects may not be dis-
cernible for days, weeks or months, as in the case of inflationary pres-
sures or the implementation of central bank monetary policies that
take time to work their way through the global economy.
To examine the multiple effects of as few as five or ten related mar-
kets simultaneously on a target market, methods such as linear cor-
relation analysis and subjective chart pattern analysis quickly reveal
their inadequacy as forecasting tools.
For most traders it is just too difficult and time consuming to keep
up with more than two or three related markets simultaneously and
to figure out how they influence each other. Two or three charts can
be “eyeballed” at the same time, or a linear correlation can be calcu-
lated between two markets at a time. However, these approaches fail
to capture the simultaneous combined effects of numerous related
markets on a specific target market.
Full Field of Vision Is Critical
You can get a sense of the difference between single-market analy-
sis and intermarket analysis if you put a hand over one of your eyes
and try walking around the room. With only one eye open, your field
of vision is limited and your ability to visualize your surroundings is
severely restricted. This is how most traders make their trading deci-
sions, with a narrow focus on each market in isolation. Next drop
your hand and walk around the room with both eyes open. Now you
are really benefiting from your full field of vision. Don’t you think you
would have an advantage if you tackle your trading the same way—
with both eyes wide open?
Here’s a different way to visualize the added depth that intermarket
analysis brings to bear on your trading decisions. Consider the case
of the Captain of the ocean liner Savvy Trader, navigating the treach-
erous waters of the north Atlantic early last century. Trying to pick the
safest route to his destination, he scanned the horizon for hazards; he
took notice of wind speed, air temperature, wave frequency and
height.
At a distance, he spotted a large floating chunk of ice. Carefully plot-
ting its speed and direction over time, he extrapolated its movement
and concluded that the ice wasn’t a threat to his ship. That night, how-
ever, the Captain was awakened by a loud crash. The iceberg had
slammed into his ship. The Captain was confused, shocked and angry.
He had not anticipated that this would happen. While meticulous-
ly examining the conditions on the surface, he was unaware of critical
conditions beneath the surface. The bulk of the massive iceberg had
been hidden from view; warming water temperatures had melted the
ice, increasing its speed. Changes in underwater currents had affected
its direction much more than surface winds. At the time (before sonar,
infrared and satellite imaging were available), the Captain did not have
tools capable of predicting the direction of the iceberg.
Trend Forecasting With Technical Analysis 53
54 Trade Secrets
A similar situation confronts today’s traders who limit themselves to
single-market analysis and lagging indicators to determine market
direction. What they are doing is not wrong; it’s simply insufficient.
Intermarket analysis tools give today’s traders the same edge in their
decisions that sonar gives today’s ship captains.
You do not need to throw the baby out with the bath water, though.
I am not suggesting that you should stop performing single-market
technical analysis or abandon the use of trend following methods that
have played a central role in technical analysis for decades.
Many popular single-market technical indicators are useful to one
degree or another to analyze internal market behavior. However, they
are most effective when used in combination with intermarket analy-
sis to get a three-dimensional view of each market. This is not a case
of “either-or.” Intermarket analysis should be used as a confirmation
filter to single-market indicators. In this manner, marginal trades can
be filtered out and avoided.
This distinction can be visualized by contrasting the rectangle on
the left side of Figure 3-4, representing single-market analysis, with
the three-dimensional cube on the right side representing intermar-
ket analysis.
Figure 3-4. INTERMARKET ANALYSIS GIVES MORE DEPTH TO YOUR ANALYSIS
Single-market analysis looks only at each market by itself. Intermarket analysis
adds a third dimension by taking into consideration the effects of related markets.
Source: Market Technologies Corporation
Intermarket analysis builds upon the strengths of single-market
analysis, adding another dimension to the analytic framework so that
the behavior of each market can be analyzed internally as well as
within a broader intermarket context.
In Figure 3-5, I have outlined some of the distinctions, from a prac-
tical trading standpoint, between intermarket analysis and single-mar-
ket analysis.
Trend Forecasting With Technical Analysis 55
Figure 3-5 INTERMARKET ANALYSIS BROADENS THE SCOPE OF SINGLE-MARKET
ANALYSIS AND OVERCOMES MANY OF ITS LIMITATIONS
Differences between intermarket analysis and single-market analysis highlight the
importance of adding intermarket analysis to your trading arsenal.
Source: Market Technologies Corporation
Intermarket Analysis With
Trend Forecasting Indicators
? Looks at multiple markets simul-
taneously. Analyzes their effects
on a target market.
? Leads the market, pinpointing
trading opportunities as they are
about to unfold.
? Traders can enter and exit trades
just as the trend is changing.
? Trends are identified as they are
developing so traders catch a big-
ger portion of each move.
? Stops are placed based on how
related markets are affecting the
market being traded.
? False trading signals are mini-
mized because the full picture is
taken into consideration, not
just a small piece of it.
Single-Market Analysis With
Trend Following Indicators
? Looks at one market at a time.
? Lags the market, causing traders
to miss the start of new trends.
? Trades are often triggered several
days after the trend has changed
direction.
? Often gives back a large portion of
profits, sometimes turning a prof-
itable trade into a losing trade.
? Stop placements are determined
by looking at the market being
traded, often based on commonly
used indicators such as trend
lines, which tend to cluster stops
near one another.
? False signals are common during
sideways markets resulting in
frequent losing trades.
56 Trade Secrets
Intermarket Analysis: In the Right Place
at the Right Time
A formal, quantitative methodology to implement intermarket
analysis, such as I have applied since 1991 within VantagePoint, is
neither a radical departure from traditional technical analysis, nor an
attempt to undermine or replace it. Intermarket analysis, in my opin-
ion, is simply the next logical developmental stage in the evolution
of technical analysis, given the global nature of today’s interdepen-
dent, highly complex economies and integrated financial markets.
If you need to dig a hole in the
ground that is a foot deep and a foot
square, you wouldn’t do it with a tea-
spoon. Similarly, if you want to stir a
cup of coffee, you wouldn’t use a
spade. You’ve got to use the right tool
for the job. Today’s markets are inter-
dependent and interconnected. That
means you need to perform intermar-
ket analysis. Let’s call a spade a spade
—single-market analysis by itself is
simply not adequate, period.
I found the best way to implement
intermarket analysis is through the use
of neural networks. They excel at find-
ing reoccurring patterns and relation-
ships between related markets, as well
as patterns within a single market. Once
found, these patterns are used to make
highly accurate forecasts of market di-
rection.
By analyzing the effects of related markets (particularly the futures
markets which are inherently oriented toward anticipating future
price levels), important early warnings of impending changes in mar-
ket direction can be gleaned from intermarket data well before these
changes begin to show up on the charts of traders who limit the
scope of their analysis to each individual market.
VantagePoint, for example, using extensive intermarket data, fore-
casts the market direction for the next two and four days and fore-
I found the best
way to implement
intermarket analy-
sis is through the
use of neural net-
works. They excel
at finding reoccur-
ring patterns and
relationships
between related
markets, as well as
patterns within a
single market. Once
found, these pat-
terns are used to
make highly accu-
rate forecasts of
market direction.
Trend Forecasting With Technical Analysis 57
warns, through its “Neural Index” indicator, whether a target market
is expected to make a top or bottom within the next two days. This
is all done automatically through the pattern recognition and fore-
casting capabilities of neural networks, which I will discuss in
Chapter 6.
Let’s face it, even my eleven-year-old son can look at a bar chart
and tell you what happened in the stock market yesterday and over
the last few days or weeks. Hindsight is 20/20; but you can only prof-
it by having foresight. You cannot make money tomorrow or next
week based on what happened yesterday or last week. You can only
make money if on a consistent basis you can anticipate, with rea-
sonable accuracy, what is going to happen in the near future.
If you had Tuesday’s Investor’s Business Daily
®
or The Wall Street
Journal
®
available to you every Monday morning with your coffee—
one day in advance—you could quickly become the wealthiest per-
son in the world. Why? Because you would have 100% accurate infor-
mation on the following day’s prices and would know exactly what
to expect next.
The Only Thing Certain Is Uncertainty Itself
Unfortunately, it is no more possible to make 100% accurate fore-
casts of the financial markets than to get The Wall Street Journal one
day in advance. Forecasting inherently involves mathematical proba-
bilities, not certainty. However, a market forecast does not need to be
perfect to tilt the odds in your favor.
To have a substantial competitive advantage over other traders, all
you need is a reliable forecast that can consistently beat a coin toss.
VantagePoint’s nearly 80% predictive accuracy at forecasting short-
term market direction gives you more than enough edge over other
traders.
Widely used technical indicators can be applied to intermarket
analysis in innovative ways. I have been very successful in accom-
plishing this with VantagePoint, in which neural networks make
short-term forecasts of moving averages.
In the next chapter I will discuss moving averages, showing you
how I turned them into a powerful leading indicator within Vantage-
Point through the use of intermarket analysis and neural networks.
TODAY’S MARKETS
HAVE CHANGED
Why Trend Forecasting Beats Trend
Following and How Traders Can Profit
M
oving averages are one of the most popular technical indi-
cators used to identify the trend direction of financial mar-
kets. Moving averages form the basis of a myriad of single-
market trend following trading strategies, ranging from the popular
4-9-18-day moving average “crossover” approach to the widely fol-
lowed 50-day and 200-day simple moving averages used to assess the
market trend direction of broad market indexes and individual stocks.
Figure 4-1, on the next page, depicts the Dow Jones Industrial
Average with its 200-day moving average superimposed on the daily
price chart. This indicator is used extensively by technicians and
traders as an indication of The Dow’s trend direction. When The Dow
closes above its 200-day moving average, the market is considered to
be in an uptrend. When The Dow closes below its 200-day moving
average, the uptrend is considered to be “broken” as a bearish senti-
ment permeates the market.
Moving averages are precisely calculated according to specific
mathematical formulae. This makes moving averages an objective
way to determine the current trend direction of a market, and antici-
pate its most likely future direction. This is in sharp contrast to sub-
jective approaches to trend identification based on visual chart analy-
sis of reoccurring patterns such as head-and-shoulder formations,
flags, triangles and pennants, etc.
Trend Forecasting With Technical Analysis 59
Chapter 4
60 Trade Secrets
Mathematically, moving averages filter out the random “noise” in
market data by smoothing out fluctuations and short-term volatility in
price movement. Graphically superimposing a moving average on a
price chart makes it easy to visualize the underlying trend within the
data.
Moving Averages Are Lagging Indicators
However, traditional moving averages have one very serious defi-
ciency. They are a “lagging” technical indicator. This means that mov-
ing averages, due to their mathematical construction (averaging prices
over a number of prior periods), tend to trail behind the current mar-
ket price. In fast moving markets, where the price is on the verge of
rising or falling precipitously, this lag effect can become very pro-
nounced and costly.
The shorter the length of a moving average, the more sensitive it
will be to short-term price fluctuations. The longer the length of a
moving average, the less sensitive it will be to abrupt price fluctua-
tions. Therefore, short moving averages lag the market less than long
moving averages, but are less effective than long moving averages at
smoothing or filtering out the noise.
Figure 4-1. FOLLOWING THE TREND OF THE DOW JONES INDUSTRIAL AVERAGE
WITH ITS 200-DAY MOVING AVERAGE
The 200-day simple moving average is a popular trend following indicator of The
Dow’s trend direction.
Source: www.bigcharts.com
Dow Jones
Industrial Average
200-day moving
average
Trend Forecasting With Technical Analysis 61
Trades based upon moving averages are often late to get into and
out of the market compared to the point at which the market’s price
actually makes a top or bottom and begins to move in the opposite
direction.
Figure 4-2 depicts a chart of daily prices of the U.S. Dollar Index
compared to its 10-day simple moving average. Because of the steep
price increase prior to the market making a top, the moving average
actually continues to increase in value, even as the market begins to
drop before cutting the moving average from above to below.
Depending on the price movement and the type and size of mov-
ing average used, this “response” delay can be financially devastating
under extreme circumstances, such as waking up one morning and
finding yourself on the wrong side of an abrupt trend reversal involv-
ing a lock-limit futures position.
The lag effect, which to date has been the Achilles’ heel of moving
averages, has presented a challenge to technical analysts and traders
for decades. Extensive research has been directed at finding ways to
reduce the lag, while at the same time retaining the benefits of mov-
ing averages.
Figure 4-2. U.S. DOLLAR INDEX WITH ITS 10-DAY SIMPLE MOVING AVERAGE
Chart of daily prices of the U.S. Dollar Index with its 10-day simple moving average
shows how moving averages lag behind the market.
Source: VantagePoint Intermarket Analysis Software
Market
made a top
here
Price
crosses
moving
average
62 Trade Secrets
To accomplish these two goals, numerous variations of moving
averages have been devised. Each has its own mathematical con-
struction, effectiveness at identifying the underlying trend of a mar-
ket and ability to overcome the lag effect. The three most common
types of moving averages relied upon by technical analysts and
traders for decades are the simple, weighted and exponential moving
averages.
Simple Moving Averages
A simple moving average is the arithmetic “mean” or average of a
price series over a selected time period. As the market moves forward
in time, the oldest price is removed from the moving average calcu-
lation and replaced by the most recent price. This allows the moving
average to “move,” thereby keeping pace with changes in the mar-
ket’s price. A simple moving average lags behind the market because
it gives equal weight to each period’s price. This limitation is what has
prompted the use of weighted and exponential moving averages.
Weighted and Exponential Moving Averages
A weighted moving average attempts to reduce the lag by giving
more weight to recent prices, thereby allowing the moving average
to respond more quickly to current market conditions. The most pop-
ular version is the linearly weighted moving average.
An exponential moving average, like a weighted moving average,
gives more weight to recent prices, while differing from a weighted
average in other respects.
Moving Averages Are Popular —
But Something’s Missing
Virtually every book on technical analysis devotes at least one
chapter to moving averages, describing detailed accounts of the var-
ious means that technicians have devised to reduce the lag effect.
While each type of moving average has its own strengths and
weaknesses at smoothing the data and reducing the lag, none of
them, by virtue of being based solely on past single-market price
data, have been successful at eliminating the lag.
Trend Forecasting With Technical Analysis 63
Using microcomputers and strategy back-testing software, since the
early 1980s traders have optimized the sizes of moving averages in an
effort to best fit them to each specific target market. For instance, the
moving average length selected for Intel might be entirely different
than for Applied Materials, Treasury notes or the Japanese yen.
In fact, the moving average length selected for a specific market at
one point in time or under certain market conditions is often differ-
ent than at other times or under other conditions. These observations
encourage traders to re-optimize moving averages periodically (and
sometimes too frequently), in a futile attempt to keep them respon-
sive to current market conditions.
Moving Average Crossovers Lead to Whipsaws
Moving averages can be used as
building blocks in more complex tech-
nical indicators, in which, for instance,
two moving averages are compared to
one another. This is done either by sub-
tracting the value of one moving aver-
age from the other or by dividing one
moving average value by the other.
Traditional moving average “crossover”
strategies are extensively relied upon by
traders to discern market direction.
A typical moving average crossover approach, for instance, involves
the calculation of two simple moving averages of different lengths,
such as a 5-day and a 10-day moving average. When the short mov-
ing average value is greater than the long moving average value, the
trend is assumed to be up. When the short moving average value is
less than the long moving average value, the trend is assumed to be
down.
Traditional moving average crossover strategies are quite effective
at filtering out market noise and identifying the current market direc-
tion in trending markets. However, in highly volatile, or choppy, non-
trending sideways markets, or even in trending markets when using
very short moving averages (which may be overly sensitive to short
term price fluctuations), these approaches tend to generate faulty
trading signals. This results in repeated “whipsaws” which can rack
Traditional moving
average crossover
strategies are quite
effective at filtering
out market noise
and identifying the
current market
direction in trend-
ing markets.
64 Trade Secrets
up trading losses as alternating buy and sell signals are triggered each
time the moving averages crisscross one another.
Some trading strategies attempt to reduce the lag by comparing an
actual price, such as the daily close, with a moving average value for
trend determination. Other strategies attempt to minimize whipsaws
by using bands surrounding the moving averages, or by including
additional moving averages to filter out false trading signals, both of
which I implemented in ProfitTaker in the early 1980s. The number
of permutations and combinations of what can be done with moving
averages is staggering.
Figure 4-3 shows the U.S. Dollar Index with its 5-day and 10-day
simple moving averages superimposed on the daily price chart. In
this case, trading decisions might be based on the short moving aver-
age crossing the long moving average (or on the close crossing one
or both of the moving averages). Notice how the turning points in the
moving averages lag behind the turning points in the market itself.
A basic assumption underlying the application of moving averages
is that a trend once in motion tends to persist. Therefore, until the
Figure 4-3. U.S. DOLLAR INDEX
A SIMPLE MOVING AVERAGE CROSSOVER APPROACH
Chart of daily prices of the U.S. Dollar Index with its 5-day and 10-day simple mov-
ing averages shows how short averages are more responsive than long averages,
but both lag behind the market.
Source: VantagePoint Intermarket Analysis Software
5-day moving average
10-day moving average
Trend Forecasting With Technical Analysis 65
long moving average is penetrated by the short moving average, for
instance, in the direction opposite from the prevailing trend, the pre-
vailing trend is assumed to still be intact.
Computing a Simple Moving Average Is Easy
The 5-day simple moving average of closes as of today’s close is
calculated by adding up the values of the most recent five days’ clos-
ing prices and dividing by 5.
Mathematically this involves adding up or “summing” the closing
prices for Day
t
+ Day
t-1
+ Day
t-2
+ Day
t-3
+ Day
t-4
, in which Day
t
is today’s Close, Day
t-1
is yesterday’s Close . . . and Day
t-4
is the Close
of the trading day four days ago. Then the sum is divided by 5.
Figure 4-4 shows a series of five daily closing prices of the Nasdaq
Composite Index and the computation of its 5-day simple moving
average.
This same approach can be used to calculate simple moving aver-
ages of various lengths, such as a 10-day moving average, a 50-day
moving average or a 200-day moving average. Additionally, prices
other than the close can be used in the computation. For instance, a
simple moving average can be computed on the High + Low divid-
ed by 2, or on the Open + High + Low + Close divided by 4. Even
intraday moving averages can be computed for various time intervals.
Figure 4-4. THE NASDAQ COMPOSITE INDEX
CALCULATING A 5-DAY SIMPLE MOVING AVERAGE OF CLOSES
Computing a simple moving average is easy. Just add up the prices and divide by
the number of days.
Source: Market Technologies Corporation
Closing Prices
Day
t-4
3384.73
Day
t-3
3499.58
Day
t-2
3529.06
Day
t-1
3607.65
Day
t
3717.57
____________
17,738.59
17,738.59 –– .
.
5 = 3547.72
= Today’s 5-Day Moving
Average of Closes
66 Trade Secrets
Displaced Moving Averages: Close But “No Cigar”
One intriguing type of moving average that attempts to overcome
the lag effect is the displaced moving average. Ordinarily when com-
puting a moving average and using it as part of a trading strategy, the
moving average value for Day
t
is plotted on a price chart in align-
ment with the closing price of Day
t
.
When this is done the lag is evident visually on the price chart as
the market trends higher, for instance, and the moving average trails
below the most recent prices. Similarly, if the market reverses abrupt-
ly and starts to trend lower, the moving average lags above the most
recent prices and briefly may even continue to increase in value as
the market declines.
A displaced moving average attempts to minimize the lag by “dis-
placing” or “shifting” the moving average value forward in time on the
chart. So, in other words, a 5-day moving average value calculated on
Day
t
(today), instead of being plotted in alignment with the price of
Day
t
, might be shifted forward (to the right) so it is plotted on the
price chart to correspond with Day
t+2
(the day after tomorrow).
Similarly, a 10-day moving average might be shifted forward four days
into the future from today to correspond with Day
t+4
.
The implicit assumption behind displacing a moving average is that
the future period’s actual moving average value (which is yet to be
determined) will turn out to be equal to today’s actual moving aver-
age value. This is, of course, a very simplistic and unrealistic assump-
tion regarding the estimate of the future period’s moving average
value. However, it is, nevertheless, a forecast —not just a linear extra-
polation from past price data such as one achieves by extending a
support or resistance line to the right of a price chart.
A New Way to Forecast Moving Averages
The fact that despite their limitations moving averages continue to
be widely used by traders is testimony that moving averages are rec-
ognized in the financial industry as an important quantitative trend
identification tool. Yet, at the same time, the inherent lagging nature
of moving averages continues to be a very serious shortcoming that
has dogged technical analysts and traders for decades.
Trend Forecasting With Technical Analysis 67
If this deficiency were somehow overcome, moving averages could
rank as the most effective trend identification and forecasting techni-
cal indicator in financial market analysis.
Since traditional moving averages are computed using only past
price data—the price for today, for yesterday, and so on—turning
points in the moving averages will always lag behind turning points
in the market.
For instance, to compute a 5-day simple moving average as of
today’s close, today’s close plus the previous four days’ closes are
used in the computation, as depicted previously in Figure 4-4 (see
page 65). These prices are already known since they have all already
occurred. The problem with this computation, from a practical trad-
ing standpoint, is that the moving aver-
age lags behind what is about to hap-
pen in the market tomorrow.
For a trader trying to anticipate what
the market direction will be tomorrow,
and determine entry and exit points for
tomorrow’s trading, any lag, however
small, may be financially ruinous given
today’s market volatility.
By comparison, a predicted 5-day
simple moving average for two days in
the future, based upon the most recent
three days’ closing prices up through
and including today’s close (which are
known values), plus the next two days’ closing prices (which have
not yet occurred) would have, by definition, no lag, if the exact clos-
ing prices for the next two trading days were known in advance.
Unfortunately, there is no such thing as 100% accuracy when it
comes to forecasting market direction or prices for even one or two
days in advance. No one will ever be able to predict the financial
markets perfectly—not now, not in a hundred years. Through finan-
cial forecasting, though, mathematical expectations of the future can
be formulated.
Needless to say, it is very challenging to predict the market direc-
tion of any financial market. The further out the time horizon, the less
reliable the forecast. That’s why I have limited VantagePoint’s fore-
No one will ever be
able to predict the
financial markets
perfectly—not now,
not in a hundred
years. Through
financial forecast-
ing, though, mathe-
matical expecta-
tions of the future
can be formulated.
68 Trade Secrets
casts to four trading days, which is more than enough lead time to
gain a tremendous trading advantage.
Trying to predict crude oil or the S&P 500 Index a month, six
months or a year from now is impractical from a trading standpoint.
This is due in part to the fact that market dynamics entail both ran-
domness and unforeseen events that are, by definition, unpredictable.
Plus, let’s face it, forecasting is not an exact science; there’s a lot of
“art” involved.
I have successfully applied neural networks to intermarket data in
order to forecast moving averages, turning them into a leading indi-
cator that pinpoints expected changes in market trend direction with
nearly 80% accuracy. This is in sharp
contrast to using moving averages as a
lagging indicator, as most traders still
do, to determine where the trend has
been.
If you are driving down an interstate
highway at seventy miles per hour, you
wouldn’t only look backwards through
your rear window or over your shoul-
der. You need to look forward, out the
front window at the road ahead, so you
can anticipate possible dangers in or-
der to prevent an accident from hap-
pening. It is the same with trading.
An enormous competitive advantage
is realized by being able to anticipate
future price action, even by just a day or two, so you can guide your
trading decisions based upon your expectation of what is about to
happen.
VantagePoint uses price, volume and open interest data on each
target futures market and selected related markets as inputs into its
neural networks. In this manner, its moving average forecasts are not
based solely upon single-market price inputs.
In the case of VantagePoint’s Nasdaq-100
®
program, for example,
the raw inputs into the forecast of the moving averages include the
daily open, high, low, close, volume and open interest for the
Nasdaq-100 Index, plus nine related markets as shown in Figure 4-5.
I have successfully
applied neural
networks to inter-
market data in
order to forecast
moving averages,
turning them into a
leading indicator
that pinpoints
expected changes in
market trend direc-
tion with nearly
80% accuracy.
Similarly, every other VantagePoint program has its own specific re-
lated markets, which provide intermarket input data into its neural
networks.
Leading Indicators Give You a
Competitive Edge
Since identifying the trend direction of a market is so critical to suc-
cessful trading of that market, trend forecasting strategies offer a sub-
stantial competitive advantage over traditional market lagging, trend
following strategies.
I have found that predicted moving averages are most effective for
trend forecasting when they are incorporated into more complex
indicators, such as moving average crossover strategies, which can be
used to identify not only the anticipated direction of the trend but
also its strength. This has been implemented within VantagePoint by
comparing predicted moving averages for certain time periods in the
future with today’s actual moving averages of the same length.
For instance, VantagePoint compares a predicted 10-day moving
average for four days in the future with today’s actual 10-day moving
average calculated as of today’s close. It also forecasts other moving
averages and makes similar comparisons, including that of a pre-
dicted 5-day moving average for two days in the future with today’s
actual 5-day moving average calculated through today’s close.
Trend Forecasting With Technical Analysis 69
Figure 4-5. INTERMARKET DATA USED BY VANTAGEPOINT’S
NASDAQ-100 PROGRAM
VantagePoint’s Nasdaq-100 program analyzes the Nasdaq-100 Index plus nine related
markets to generate intermarket-based forecasts.
Source: Market Technologies Corporation
• Dow Jones Industrial Average
• 30-Year Treasury Bonds
• S&P 500 Index
• U.S. Dollar Index
• S&P 100
®
• NYSE Composite Index
®
• Bridge/CRB Index
• Dow Jones Utility Average
SM
• Light Crude Oil
70 Trade Secrets
Figure 4-6 shows a crossover of the predicted 10-day moving aver-
age and the actual 10-day moving average for the Dow Jones Indus-
trial Average. Notice that the predicted moving average, because it is
being forecasted for four days in advance, does not lag behind the
market, while the actual 10-day moving average lags behind both the
market and the predicted moving average.
The leading indicators within VantagePoint, involving the crossover
of predicted moving averages with actual moving averages, will be
discussed in more detail in the next chapter.
Figure 4-6. DOW JONES INDUSTRIAL AVERAGE
USING A PREDICTED MOVING AVERAGE CROSSOVER STRATEGY
Chart of daily prices of The Dow with a 10-day predicted moving average and 10-day
actual moving average crossover. Notice the difference in lag between the predicted
and actual moving averages.
Source: VantagePoint Intermarket Analysis Software
Predicted 10-day mov-
ing average, forecasted
4 days into the future
Actual 10-day
moving average
VANTAGEPOINT FORECASTS
MARKET DIRECTION
How to Get a Sneak Preview of Where the
Markets Are Going and Use This
Information to Your Advantage
V
antagePoint uses the pattern recognition capabilities of neural
networks to analyze market data from each target market plus
selected related markets in order to make forecasts for that tar-
get market. This is accomplished by predicting short-term moving
averages, which are then used to indicate the market direction of
each target market.
Since 1991 when VantagePoint was first introduced, Market Tech-
nologies Corporation’s research team, the Predictive Technologies
Group, under my direction has continued to conduct proprietary
research and development with neural networks and intermarket
analysis. Updated versions of VantagePoint have been released as
improvements in its forecasting accuracy have been achieved.
VantagePoint Monitors Major Financial Markets
Presently there are twenty-five actively traded financial markets that
VantagePoint monitors each day. These include interest rates, stock in-
dexes, energies and currencies, as presented in Figure 5-1 on page 72.
With its ability to make consistently accurate trend forecasts for
these actively traded financial markets, VantagePoint offers a competi-
tive advantage, from an intermarket perspective, to serious traders in
Trend Forecasting With Technical Analysis 71
Chapter 5
72 Trade Secrets
the futures, options and equity markets. It’s not a crystal ball, but it
may be the next best thing.
Many VantagePoint clients day trade while others position trade or
do a combination of both. Some clients trade full-time while others,
employed outside the financial industry, trade part-time.
Typically VantagePoint is used by traders in conjunction with other
technical trading tools that they are already using. In this way Van-
tagePoint’s predictive indicators act as intermarket confirmation filters
to various single-market indicators that only look internally at each
market.
When VantagePoint confirms these single-market indicators from
an intermarket perspective, that’s a green light to take the trade.
However, when VantagePoint is in disagreement with these single-
market indicators, that’s a bright yellow caution light.
FIGURE 5-1. FINANCIAL MARKETS COVERED BY VANTAGEPOINT
VantagePoint monitors interest rate, stock index, energy and currency markets, giv-
ing intermarket-based forecasts.
Source: Market Technologies Corporation
30-Year T-Bonds
10-Year T-Notes
5-Year T-Notes
2-Year T-Notes
Eurodollar
INTEREST RATES
S&P 500
S&P 100
FTSE 100
Nikkei
Nasdaq-100
Nasdaq Composite
Dow
STOCK INDEXES
Gasoline
Natural Gas
Gas Oil
Brent Crude
Light Crude
Heating Oil
ENERGIES
Swiss Franc
Deutsche Mark
British Pound
Canadian Dollar
Australian Dollar
U.S. Dollar Index
Japanese Yen
CURRENCIES
After spending a little time becoming familiar at first with its reports
and charts, it takes just a few minutes each day to update Vantage-
Point and have its predictive intermarket-based information available
for making your trading decisions.
Figure 5-2 lists the predictive accuracy of VantagePoint’s trend fore-
casts, based on its proprietary Neural Index indicator (which will be
discussed later), for each of the twenty-five financial markets cur-
rently monitored by VantagePoint.
Five Neural Networks Make Independent Forecasts
Each VantagePoint program is specifically designed for a particular
target market and uses five neural networks, in a two-level hierarchy,
to forecast five different leading indicators for that market.
Trend Forecasting With Technical Analysis 73
FIGURE 5-2. PREDICTIVE ACCURACY OF VANTAGEPOINT’S TREND FORECASTS
In the financial markets, 100% predictive accuracy is not attainable. With random-
ness and unforeseen events, perhaps only 80-85% is realistically possible.
30-Year T-Bonds 74.60%
10-Year T-Notes 76.10%
5-Year T-Notes 81.67%
2-Year T-Notes 72.20%
Eurodollar 73.90%
INTEREST RATES
S&P 500 76.60%
S&P 100 78.40%
FTSE 100 74.57%
Nikkei 70.80%
Nasdaq-100 75.40%
Nasdaq Composite 78.56%
Dow 78.09%
STOCK INDEXES
Gasoline 73.00%
Natural Gas 73.70%
Gas Oil 81.33%
Brent Crude 73.67%
Light Crude 76.64%
Heating Oil 70.70%
ENERGIES
Swiss Franc 72.50%
Deutsche Mark 76.02%
British Pound 77.10%
Canadian Dollar 76.67%
Australian Dollar 77.50%
U.S. Dollar Index 76.67%
Japanese Yen 74.66%
CURRENCIES
Source: Market Technologies Corporation
74 Trade Secrets
• The first network forecasts tomorrow’s High, to help set stops for
entry and exit points.
• The second network forecasts tomorrow’s Low, to help set stops for
entry and exit points.
• The third network forecasts a 5-day moving average of closes for
two days in the future, to indicate the expected Short-Term trend
direction within the next two days.
• The fourth network forecasts a 10-day moving average of closes for
four days in the future, to indicate the expected Medium-Term
trend direction within the next four days.
• The fifth network indicates if the market is expected to change
trend direction by making a top or bottomwithin the next two days.
The first four networks at the primary
level of the network hierarchy make in-
dependent market forecasts of the High,
Low, Short-Term trend and Medium-
Term trend. These forecasts are then
used as inputs into the fifth network
along with other target market and inter-
market data inputs, at the secondary
level of the network hierarchy, to predict
market Turning Points. VantagePoint’s
neural network configuration is shown
in Figure 5-3 (see page 75).
While the underlying mathematics behind VantagePoint is very
complex, its forecasted intermarket-based trading information is easy
to understand. Even a new trader with no background in mathemat-
ics or technical analysis can begin to benefit immediately from its
information. VantagePoint is designed for active traders, not engineers
or rocket scientists.
VantagePoint’s forecasts are presented for each target market in a
one-page Daily Report. A more detailed History Report is also avail-
able for more in-depth analysis. VantagePoint’s predictive information
is also exportable to other software programs. Additionally, all of the
indicators presented in the Daily Report can be displayed or printed
as detailed color charts, for traders who are more visually oriented.
Figure 5-4 (see page 76) shows a VantagePoint chart of the Dow
Jones Industrial Average with its predicted 10-day moving average
While the under-
lying mathematics
behind Vantage-
Point is very
complex, its fore-
casted intermarket-
based trading
information is easy
to understand.
and actual 10-day moving average superimposed on the daily prices.
In this example, the entry point to go long occurs when the predict-
ed moving average crosses the actual moving average from below to
above as indicated by the “up arrow” at the left of the chart. The long
position is maintained until the predicted moving average crosses the
actual moving average from above to below as indicated by the
“down arrow” at the right of the chart.
Trend Forecasting With Technical Analysis 75
FIGURE 5-3. VANTAGEPOINT’S FIVE NEURAL NETWORKS
VantagePoint makes five different forecasts for each target market using five sepa-
rate neural networks. There’s a lot of horsepower under the hood, but you don’t have
to be a race-car driver to get your intermarket driver’s license. VantagePoint is de-
signed for traders, not rocket scientists.
Source: Market Technologies Corporation
Network 1
Network 2
Predicted
High
Predicted
Low
Predicted
Short Trend
Predicted
Medium
Trend
Neural
Index
Predicted
Turning
Points
Network 3
Network 4
Network 5
76 Trade Secrets
Figure 5-4. THE DOW JONES INDUSTRIAL AVERAGE
CROSSOVER OF PREDICTED AND ACTUAL MOVING AVERAGES
A simple moving average crossover strategy with a twist —it compares a predicted
10-day moving average with an actual 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
1,155 point trade = $11,550
Predicted 10-day
moving average
Actual 10-day
moving average
Figure 5-5 (see page 77) shows a sample VantagePoint Daily Report
for the Nasdaq Composite Index. Notice that the report is divided into
three sections, each of which will be discussed in detail shortly.
Figure 5-6 (see page 77) shows a sample VantagePoint History
Report for the Nasdaq Composite Index.
The layout, information and interpretation of a VantagePoint chart
or report for one target market are identical to those for each of the
other target markets. Therefore, once you are familiar using Vantage-
Point on one market, it is simple to use it on others. In fact, Vantage-
Point is designed so that it can be updated on all twenty-five markets
automatically at the touch of your mouse button. The whole process
takes just a few minutes each day.
What VantagePoint’s Daily Report Tells You
Each Daily Report gives you intermarket-based forecasts for use on
the next trading day, in addition to information from previous days to
give some background on what has just happened in that market.
FIGURE 5-5. A SAMPLE NASDAQ COMPOSITE DAILY REPORT
VantagePoint’s Daily Report is divided into three sections.
Source: VantagePoint Intermarket Analysis Software
FIGURE 5-6. A SAMPLE NASDAQ COMPOSITE HISTORY REPORT
VantagePoint’s History Report offers more detailed analysis.
Source: VantagePoint Intermarket Analysis Software
78 Trade Secrets
Figure 5-7 displays Section 1 of a VantagePoint Daily Report for the
10-year Treasury notes program.
Section 1 displays the following information:
• Today’s actual Open, High, Low, Close.
• Today’s actual 5-day simple moving average of closes. This is
labeled TrndS (for Trend Short).
• Today’s actual 10-day simple moving average of closes. This is
labeled TrndM (for Trend Medium).
Figure 5-8 (see page 79) displays Section 2 of a VantagePoint Daily
Report for the 10-year Treasury notes program.
Section 2 displays the following information:
• Tomorrow’s predicted High. This is labeled PHigh.
• Tomorrow’s predicted Low. This is labeled PLow.
• Predicted 5-day simple moving average of closes for two days in the
future. This is labeled PTS (for Predicted Trend Short). Three of the
closing prices (today, yesterday and the day before yesterday) are
FIGURE 5-7. 10-YEAR TREASURY NOTES—SECTION 1 OF THE DAILY REPORT
Section 1 of the Daily Report displays the Open, High, Low, Close, actual 5-day and
actual 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
Open High Low Close TrndS TrndM
4/24/00 9816 9840 9812 9816 9806 9819
4/25/00 9816 9816 9732 9734 9802 9808
4/26/00 9732 9754 9730 9736 9763 9802
4/27/00 9734 9748 9646 9654 9744 9759
4/28/00 9656 9712 9630 9662 9728 9750
5/01/00 9660 9702 9644 9646 9708 9739
5/02/00 9646 9656 9626 9628 9658 9730
5/03/00 9626 9638 9558 9562 9638 9718
5/04/00 9600 9608 9532 9536 9621 9701
5/05/00 9540 9562 9512 9518 9600 9646
5/08/00 9518 9534 9460 9500 9542 9625
5/09/00 9460 9520 9456 9516 9526 9610
Actual 5-day
moving average
Actual 10-day
moving average
Trend Forecasting With Technical Analysis 79
FIGURE 5-8. 10-YEAR TREASURY NOTES—SECTION 2 OF THE DAILY REPORT
Section 2 of the Daily Report displays the predicted High, predicted Low, predicted
5-day moving average and predicted 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
PHigh PLow PTS PTM
4/24/00 9829 9800 9812 9816
4/25/00 9747 9712 9752 9751
4/26/00 9755 9724 9743 9748
4/27/00 9704 9630 9710 9725
4/28/00 9723 9646 9701 9723
5/01/00 9703 9632 9650 9701
5/02/00 9645 9616 9640 9652
5/03/00 9612 9543 9614 9637
5/04/00 9550 9518 9554 9619
5/05/00 9533 9502 9531 9601
5/08/00 9519 9448 9513 9546
5/09/00 9535 9462 9512 9537
Predicted 5-day
moving average
Predicted trading
range for the next day
Predicted 10-day
moving average
known since they have already occurred up through today’s close.
The remaining two closing prices (for tomorrow and the day after
tomorrow) are not known since they have not yet occurred.
• Predicted 10-day simple moving average of closes for four days in
the future. This is labeled PTM (for Predicted Trend Medium), in
which six of the closing prices are known, but the remaining four
closing prices are not known.
Figure 5-9 (see page 80) displays Section 3 of a VantagePoint Daily
Report for the 10-year Treasury notes program.
Section 3 displays the following information:
• The Strength Index, a weighted composite of the four indicators from
Section 2, indicates if the market is getting overbought or oversold.
• PHigh Diff displays the difference between the predicted High for
tomorrow from Section 2, and today’s actual High from Section 1.
• PLow Diff displays the difference between the predicted Low for
tomorrow from Section 2, and today’s actual Low from Section 1.
80 Trade Secrets
• The Neural Index indicates whether or not the market is expected
to make a top or bottom and change trend direction within the next
two days, based on a comparison of two 3-day moving averages.
• PTS Diff displays the difference between the predicted 5-day mov-
ing average for two days in the future (PTS) from Section 2, and
today’s actual 5-day moving average (TrndS) from Section 1.
• PTM Diff displays the difference between the predicted 10-day
moving average for four days in the future (PTM) from Section 2,
and today’s actual 10-day moving average (TrndM) from Section 1.
Intermarket Charts Show You What’s Ahead
VantagePoint has extensive charting capabilities to help you visu-
alize its forecasts of market trend direction and prices. This is really
what makes VantagePoint so unique.
FIGURE 5-9. 10-YEAR TREASURY NOTES—SECTION 3 OF THE DAILY REPORT
Section 3 of the Daily Report displays the Strength Index, differences between the
predicted indicators and today’s actual indicators, and the Neural Index. This sec-
tion alerts you to an impending change in market direction and strength.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
Strength PHighDiff PLowDiff Index PTSDiff PTMDiff
4/24/00 -0.36 -11 -12 1.00 6 -3
4/25/00 -0.70 -33 -20 0.00 -14 -21
4/26/00 -0.45 1 -6 0.00 -20 -18
4/27/00 -0.73 -44 -16 0.00 -34 -34
4/28/00 0.15 11 16 0.00 -27 -27
5/01/00 -0.50 1 -12 0.00 -22 -38
5/02/00 -0.69 -11 -10 0.00 -18 -42
5/03/00 -0.72 -26 -15 0.00 -24 -45
5/04/00 -0.72 -22 -14 0.00 -31 -46
5/05/00 -0.72 -29 -10 0.00 -33 -45
5/08/00 -0.71 -15 -12 0.00 -29 -43
5/09/00 0.09 15 6 0.00 -14 -37
PTS Diff becomes negative indicating weakness
Index turns to 0.00
indicating weakness
PTM Diff becomes
more negative
indicating further
weakness
Trend Forecasting With Technical Analysis 81
Unlike traditional charts, VantagePoint’s charts show you where it
expects the market to go next, not just where it has been in the past.
While other traders are still relying solely upon single-market trend
following indicators, which look backward and can only identify
trend changes after the fact, VantagePoint lets you look forward so
you get a sneak preview of what’s ahead. This is like having a road
map that other traders can’t decipher because they don’t know the
secret code.
VantagePoint has two modes of chart presentation: Overlay and
Displaced.
• In Overlay mode, the predicted indicator is plotted on the day that
the prediction is made.
• In Displaced mode, the indicator is plotted on the day for which it
is predicted rather than on the day the prediction is made.
Figure 5-10 displays a VantagePoint chart showing the predicted
10-day moving average of the 10-year Treasury notes plotted in
Overlay mode. This indicator predicts what the 10-day moving aver-
age value will be four days in the future. Notice how turns in the pre-
dicted moving average do not lag behind turns in the market itself.
Figure 5-10. PREDICTED 10-DAY MOVING AVERAGE IN OVERLAY MODE
Chart of daily prices of 10-year Treasury notes with its predicted 10-day moving
average plotted in Overlay mode.
Source: VantagePoint Intermarket Analysis Software
Predicted 10-day
moving average
Figure 5-11 displays a VantagePoint chart showing the next day’s
predicted High and Low of the Dow Jones Industrial Average plotted
in Displaced mode onto the actual day that corresponds to the pre-
dictions. These price forecasts are used by traders to determine entry
and exit points, which will be discussed later in this chapter.
VantagePoint Is Quick and Easy
Each evening after the markets close, that day’s open, high, low,
close, volume and open interest data on each target market and its
nine related markets are downloaded from a VantagePoint-compatible
data vendor’s database or over the Internet. When you perform the
Daily Update function within VantagePoint this information is auto-
matically processed by VantagePoint’s five neural networks which
then generate their forecasts for the next day’s trading.
All you have to do is compare the Daily Reports (or charts) for sev-
eral target markets to one another, to see which markets offer the best
trades to take the next day. The process takes only a few minutes
from start to finish. If there is not a clear-cut indication of market
direction, you would pass on taking a trade in that particular market.
82 Trade Secrets
Figure 5-11. PREDICTED HIGH AND LOW IN DISPLACED MODE
Chart of Dow Jones Industrial Average with its predicted High and Low plotted in
Displaced mode on the actual day that corresponds to the predictions.
Source: VantagePoint Intermarket Analysis Software
Predicted High
Predicted Low
Trend Forecasting With Technical Analysis 83
Only those trades with the highest probability of success should be
taken. This stacks the odds in your favor.
Let’s look at the steps to follow in determining whether or not a
trade is worth taking.
How to Find a Good Trade
The Neural Index in Section 3 of the Daily Report is a good place
to start to get an indication of the expected market trend direction.
The Neural Index is a proprietary indicator, determined by compar-
ing two 3-day moving averages to one another:
• Today’s actual 3-day moving average,
which is the sum of today’s close
(Day
t
), yesterday’s close (Day
t-1
) and
the close of the day prior to yester-
day’s close (Day
t-2
) divided by 3.
• A predicted 3-day moving average,
which is the sum of today’s close
(Day
t
), tomorrow’s close (Day
t+1
)
and the close of the day after tomor-
row (Day
t+2
) divided by 3.
The forecast of the predicted 3-day
moving average is made by Vantage-
Point’s fifth neural network, using pre-
dictions from the other four networks as
inputs, in addition to data from the tar-
get market itself and the specific related
markets pertaining to that target market.
When the predicted 3-day moving average value is greater than
today’s actual 3-day moving average value, the Neural Index is 1.00.
This indicates that VantagePoint expects the market to move higher
over the next two days.
When the predicted 3-day moving average value is less than today’s
actual 3-day moving average value, the Neural Index is 0.00. This indi-
cates that the market is expected to move lower over the next two
days.
With an overall predictive accuracy rate of nearly 80% as indicated
in Figure 5-2 (see page 73), the Neural Index will give you added
The Neural Index in
Section 3 of the
Daily Report is a
good place to start
to get an indication
of the expected
market trend direc-
tion. The Neural
Index is a propri-
etary indicator,
determined by com-
paring two 3-day
moving averages to
one another.
84 Trade Secrets
confidence to pull the trigger when there is a strong indication that a
market is about to make a top or bottom and poised to change trend
direction.
Here’s How to Get Added Confirmation
You can use the PTS Diff and the PTM Diff indicators in Section 3
of the Daily Report in conjunction with the Neural Index to confirm
the expected market direction. The strongest confirmation occurs
when the Index, PTS Diff and PTM Diff are in agreement with each
other.
Each day as VantagePoint’s neural networks are updated with the
most recent data on the target market and its related markets, Van-
tagePoint makes its forecasts and calculates the difference in value
between each predicted moving average and the actual moving aver-
age of the same length. By using forecasted moving averages, Van-
tagePoint retains all of the smoothing effects of moving averages,
while effectively eliminating the lag.
When the predicted moving average crosses above the actual mov-
ing average (the PTS Diff or PTM Diff turns positive), VantagePoint
expects the market trend to turn up within the forecast time horizon
related to each of these two indicators.
• When the PTS Diff is positive, reaches a maximum positive value
and narrows (indicating that the upward trend is beginning to lose
strength), this gives you an early warning that the market is about
to make a top and turn down within the next two days.
• When the PTM Diff is positive, reaches a maximum positive value
and narrows (indicating that the upward trend is beginning to lose
strength), this gives you an early warning that the market is about
to make a top and turn down within the next four days.
Similarly, when the predicted moving average crosses below the
actual moving average (the PTS Diff or PTM Diff turns negative),
VantagePoint expects the market trend to turn down within the fore-
cast time horizon related to each of these two indicators.
• When the PTS Diff is negative, reaches a maximum negative value
and narrows (indicating that the downward trend is beginning to
lose strength), this gives you an early warning that the market is
about to make a bottom and turn up within the next two days.
• When the PTM Diff is negative, reaches a maximum negative value
and narrows (indicating that the downward trend is beginning to
lose strength), this gives you an early warning that the market is
about to make a bottom and turn up within the next four days.
Rather than wait for the crossover to actually occur, you can make
trading decisions based on the narrowing in the PTS Diff or PTM Diff,
which is the earliest warning that the market trend is beginning to lose
strength. For instance, if you are in a long position, you can act on this
information in a number of ways depending on your account size, risk
propensity, information derived from
single-market technical indicators that
you also utilize, your trading style and
objectives. Here are just three possible
strategies that can be implemented:
• If the PTS Diff or PTM Diff reaches a
maximum positive value and narrows
by even a small amount, you can
close out your long position and
stand aside. Then you can wait for
either the PTS Diff or PTM Diff to nar-
row further or wait for one or both of
them to turn negative before taking a
short trade, even if the Neural Index
has still not changed to 0.00. If either
the PTS Diff or PTM Diff (or both)
instead show renewed strength (the
difference between the predicted and
the actual moving average value
widens again instead of continues to narrow), you could re-enter
your long position.
• If the PTS Diff or PTM Diff reaches a maximum positive value and
narrows by even a small amount and the Index is 1.00, you can
tighten your stop and stay in your long position. With this strategy
you are still long should the market show renewed strength. If,
instead, the difference continues to narrow on subsequent days,
you would close out your long position and stand aside or reverse
positions.
• If the PTS Diff or PTM Diff reaches a maximum positive value and
narrows by a predetermined minimum amount, you can close out
Trend Forecasting With Technical Analysis 85
You can use the
PTS Diff and the
PTM Diff indicators
in Section 3 of the
Daily Report in
conjunction with
the Neural Index
to confirm the
expected market
direction. The
strongest confirma-
tion occurs when
the Index, PTS Diff
and PTM Diff are in
agreement with
each other.
86 Trade Secrets
your long position and go short, even if the Index has still not
changed to 0.00. This strategy is the most aggressive of the three
since it involves reversing positions at the earliest indication that the
current market trend is likely to make a top and change direction.
Likewise, if you are short you would wait for the PTS Diff or PTM
Diff to reach a maximum negative value and narrow before follow-
ing one of these three strategies.
To the extent that the PTS Diff and PTM Diff behave similar to each
other from one day to the next (and are confirmed by the Neural
Index), you can be more confident that the market will move as
expected within the forecast time horizons of these three indicators.
By creating trend forecasting strategies, which compare predicted
moving averages with actual moving averages, you can get an early
warning of an impending change in trend direction—days before it
would show up on a traditional price chart or be identified by single-
market trend following indicators such as lagging moving average
crossover approaches.
Here’s a Simple Example
Figure 5-12 is an example
of a 10-year Treasury notes
trade. In practice, each day
after you update Vantage-
Point you would see the lat-
est Index, PTS Diff and PTM
Diff values in Section 3 of
that day’s Daily Report.
For the purpose of this
example, the more conserva-
tive trading strategy of wait-
ing for the Index to change
from 1.00 to 0.00, and for the PTS Diff and PTM Diff to both turn neg-
ative before entering a short trade will be examined. Therefore the
following relatively stringent conditions, which indicate that the mar-
ket is likely to make a top and that weakness is about to set in, will
need to be met:
• If the Index value is 1.00 indicating that the market is in an up
trend, you would wait for the Index to change to 0.00.
Figure 5-12. VANTAGEPOINT PREDICTS A
MARKET TOP AS MARKET
SHOWS STRENGTH
Changes in the Index, PTS Diff and PTM Diff
over a five-day period warn that the market
is about to make a top and turn down.
Source: Market Technologies Corporation
Index PTS Diff PTM Diff
4/24/00 1.00 6 -3
4/25/00 0.00 -14 -21
4/26/00 0.00 -20 -18
4/27/00 0.00 -34 -34
4/28/00 0.00 -27 -27
• If the PTS Diff is positive indicating that the market is in an up trend,
you would wait for the PTS Diff to narrow and turn negative.
• If the PTM Diff is positive indicating that the market is in an up trend,
you would wait for the PTM Diff to narrow and turn negative.
After the close on 4/24/00 VantagePoint reported an Index value of
1.00, a PTS Diff of 6, and a PTM Diff of –3. While the market showed
strength, with progressively higher highs and higher lows on 4/19/00,
4/20/00 and 4/24/00, the negative PTM Diff on 4/24/00 is the first
clear cut confirmation that the market is expected to weaken and turn
down.
After the close on 4/25/00, the Index changed from 1.00 to 0.00
and the PTS Diff changed from 6 to –14, confirming the weakness
that was indicated on 4/24/00 by the negative PTM Diff. In fact, on
4/25/00 the PTM Diff indicated even
further expected weakness, as it
changed from –3 to –21. When these
three leading indicators confirm each
other like this, it is a strong indication
that a short position can be taken. The
expectation of impending weakness
was reaffirmed after the close on
4/26/00, when the Index remained at
0.00 and the PTS Diff changed from -14
to –20.
Once the Index changes from 1.00 to
0.00 and the PTS Diff and PTM Diff
change from positive to negative, fur-
ther weakness is indicated on subse-
quent days if the Index remains at 0.00 and the PTS Diff and PTM
Diff become even more negative. This is what happened after the
close on 4/27/00, when the Index remained at 0.00 and both the PTS
Diff and PTM Diff changed to -34 in value.
The opposite scenario suggests taking a long position. This hap-
pens when the Index changes from 0.00 to 1.00 and the PTS Diff and
PTM Diff are negative and start to narrow by getting less negative,
before changing to positive values. For even more confirmation, the
Strength Index can be used to determine the extent to which the mar-
ket is getting overbought (large positive values) or oversold (large
negative values).
Trend Forecasting With Technical Analysis 87
By creating
trend forecasting
strategies, which
compare predicted
moving averages
with actual moving
averages, you
can get an early
warning of an
impending change
in trend direction.
88 Trade Secrets
Day and Position Trading With Tomorrow’s
Price Forecasts
Once you have identified the expected trend direction using the
Index, PTS Diff and PTM Diff from Section 3 of the Daily Report, you
can set your entry point, by looking at the next day’s predicted High
and predicted Low in Section 2 of the Daily Report. These price fore-
casts create an expected trading range for the next day, which is anal-
ogous to extending support and resistance lines in traditional single-
market technical analysis approaches.
The advantage of VantagePoint, though, is that the next day’s High
and Low forecasts, based on the pattern recognition capabilities of
neural networks applied to intermarket data, are objectively deter-
mined and are not just an arbitrary linear extrapolation from past sin-
gle-market data.
If you are a day trader, you can use the forecasts of the next day’s
High and Low to identify low-risk day trades. If the Neural Index and
forecasted moving average indicators for a specific target market indi-
cate that the next day is expected to be a down day, you can wait for
the market to trade up toward the predicted High before initiating a
short position with a limit or market order, with the intention of clos-
ing out the trade near the predicted Low.
The left side of Figure 5-13 (see page 89) displays the forecast
made after the close on 4/25/00 for the High on 4/26/00 to be 9747
for 10-year Treasury notes. VantagePoint also forecasted this market
to go down on 4/26/00, indicating that day traders can enter short
positions near the predicted High. The right side of Figure 5-13 shows
what actually happened on 4/26/00.
Similarly, long positions can be entered near the predicted Low on
a day expected to be up, with exits near the predicted High. This
allows day traders to sell rallies within an expected downtrend or buy
dips within an expected uptrend, one or more times daily depending
on the intraday market volatility. The profitability of day trades that
are executed with this strategy can be substantial with minimal risk,
since tight stops can be utilized.
If you are a position trader, you can use the forecasts of the next
day’s High and Low to enter positions, then use the subsequent days’
forecasts to move your stop or exit the trade. For example, let’s say
it’s 4/25/00 and you just looked at tonight’s Daily Report and every-
thing indicates a bearish bias for the next day. You decide you want
to go short on 4/26/00. You
can determine where you
should enter the market by
looking at the predicted
High for 4/26/00, as shown
on the Daily Report of
4/25/00 in Figure 5-14. In
this case you could enter a
short position at or near
9747.
Stop Placement Based on Forecasts Not Hunches
You could put a protective buy stop somewhere above the pre-
dicted High of 9747 depending on your risk propensity so your stop
is sufficiently outside of the daily range that VantagePoint forecasts
for 4/26/00. This would lessen the probability of being stopped out
Trend Forecasting With Technical Analysis 89
Figure 5-13. DAY TRADERS USE VANTAGEPOINT’S PRICE FORECASTS
FOR QUICK TRADES
VantagePoint forecasts this market to go down on 4/26/00. Day traders can enter a
short position near the predicted High of 9747, covering the short before the end of
the day.
Source: Market Technologies Corporation
4/25/00
? VantagePoint forecasts the market
to go down on the next day
(4/26/00).
? VantagePoint forecasts the High
on the next trading day (4/26/00)
to be 9747.
? Traders should look to go short
near 9747.
Open:
9732
Low: 9730
Close: 9736
High: 9754
Predicted
High: 9747
Generated on
4/25/00 for trading
on 4/26/00.
4/26/00
Figure 5-14. PREDICTED HIGH AND LOW
IN SECTION 2
Position traders can enter short positions
near the predicted High, and stay in the
position until the market is expected to
make a bottom.
Source: Market Technologies Corporation
PHigh PLow
4/25/00 9747 9712
90 Trade Secrets
prematurely due to intraday market volatility, yet protect you in the
event the market penetrates the predicted High and breaks out to the
upside.
The benefit of setting your stop based on forecasts of the next day’s
High or Low is that your stop is less likely to be clustered among
other traders’ stops which are typically set through traditional meth-
ods of single-market analysis such as extending support and resis-
tance trend lines.
As a position trader you would stay in your short position until the
following day. Then if VantagePoint indicates continued expected
weakness on the Daily Report updated after the close of 4/26/00 (to
be used for trading on 4/27/00), you would hold the short position
for another day. In this case the market opened at 9734 on 4/27/00
and ended up closing substantially lower at 9654 as shown previously
in Figure 5-7 (see page 78). In fact, from Figure 5-9 (see page 80) you
can see that the Index, PTS Diff and PTM Diff all indicated sustained
weakness through 5/8/00 as Treasury notes moved lower by nearly
three points.
Other Markets Give Added Confirmation
Since the neural networks for each VantagePoint program have
been developed and trained independently for each particular target
market, daily reports from other target markets can be used for addi-
tional confirmation.
Once you are familiar with one Daily Report, and understand what
to look for in terms of the PHigh, PLow, Neural Index, PTS Diff and
PTM Diff, it is simple to understand the Daily Reports for other mar-
kets monitored by VantagePoint.
The eurodollar, 2-year Treasury notes, 5-year Treasury notes and
the 30-year Treasury bonds daily reports, for example, add consider-
able insight into what is likely to happen to 10-year Treasury notes,
since these five markets taken together encompass the entire interest
rate yield curve from ninety days to thirty years.
The more the forecasted indicators on these other reports confirm
the indicators on the 10-year Treasury notes Daily Report, the higher
the probability that the Treasury notes market will act as expected.
On the other hand, if these other reports give contrary indications,
you should be cautious. Similar confirmations or divergences can be
found among the energy markets, stock indexes and currencies mon-
itored by VantagePoint.
Even traders who do not trade futures but only buy and sell indi-
vidual stocks (such as new economy technology stocks comprising
the Nasdaq Composite Index or old economy stocks comprising The
Dow) can use VantagePoint’s Nasdaq and Dow programs for timing
individual stock transactions.
How To “Cherry-Pick” the Best Trades to Take
With VantagePoint programs covering major financial markets,
traders with multiple programs can pick only those trades to take
each day that have the highest probability of being profitable. I call
this “cherry-picking.” This lets you avoid the trap that many other
traders fall into, in which they feel compelled to trade even when
there isn’t a good trade to be taken. So they chase after marginal
trades, with predictably negative results.
If you can appreciate the advantage of having intermarket-based
trend forecasts with nearly 80% accuracy at predicting short-term
market direction, and the benefit of broadening your perspective of
the markets beyond simply focusing on the internal dynamics within
each individual market, then you will become a believer in intermar-
ket analysis and the power of neural networks as a market forecast-
ing tool.
In the next chapter I will explain very briefly in non-mathemati-
cal terms what neural networks are and how they can be utilized as
a forecasting tool to predict the market direction of any financial
market.
Trend Forecasting With Technical Analysis 91
NEURAL NETWORKS
How to Raise Your Financial IQ to
Stay Ahead of the Competition
T
he human brain is composed of hundreds of billions of cells
known as neurons, which through their connections to each
other relay information from one neuron to another. This pro-
cess allows a person to learn relationships, draw inferences, recog-
nize patterns and make predictions, among other tasks. While sub-
stantially less complex than the human
brain, neural networks model how it
processes information and performs
pattern recognition and forecasting.
Neural networks are comprised of
individual neurons organized in layers
and interconnected through network
architecture with variable mathematical
weights attributed to each connection.
The architecture includes an input layer,
hidden layer and an output layer.
Neural networks are excellent at sift-
ing through enormous amounts of seem-
ingly unrelated market data and finding
repetitive patterns that could never be
perceived visually just by looking at
price charts or by comparing two markets to one another. Through a
mathematical error minimization process known as “learning” or
“training,” neural networks, if designed properly, can be trained to
make highly accurate market forecasts based upon these patterns.
Trend Forecasting With Technical Analysis 93
Chapter 6
Neural networks
are excellent at
sifting through
enormous amounts
of seemingly unre-
lated market data
and finding repeti-
tive patterns that
could never be
perceived visually
just by looking at
price charts or by
comparing two mar-
kets to one another.
FIGURE 6-1. VANTAGEPOINT’S NEURAL NETWORKS MAKE MARKET FORECASTS
Source: Market Technologies Corporation
94 Trade Secrets
Neural Networks Combine Technical and
Intermarket Data
VantagePoint’s neural networks are designed and trained to make
specific forecasts for each target market. The raw input data from the
target market and related markets, statistical “preprocessing” of the
raw data, network architecture, as well as the training and testing reg-
imens are tailored to each target market.
Figure 6-1 depicts how single-market technical data from a target
market and intermarket data from related markets are fed into
VantagePoint’s neural networks to make predictions for each of the
twenty-five target markets that VantagePoint monitors each day.
Like back-testing and optimization a decade earlier, neural net-
works at first had their skeptics and detractors in the financial indus-
try in the early 1990s, around the time the first version of Vantage-
Point was released. Software developers from outside of the financial
industry, knowledgeable about neural networks applied to other are-
nas and perceiving a potentially lucrative marketplace for their soft-
ware among traders, flooded into the financial industry offering an
assortment of neural network software programs to traders. Before
long neural networks were being hyped in promotional marketing lit-
erature as the Holy Grail of technical analysis as expectations about
their potential reached dizzying heights.
Single-market technical data and intermarket data from related markets are fed into
VantagePoint’s neural networks to make forecasts for the target market.
Data From
Target Market
Data From
Related
Markets
Neural
Networks
Goal
Trend
Forecasts
and
Price
Forecasts
Unfamiliar with the intricacies of the financial markets and the
details underlying technical analysis, many of these newcomers to the
financial industry helped foster a backlash against neural networks
among traders as the Holy Grail remained elusive.
My focus, though, since the mid-1980s has been intermarket analy-
sis. Neural networks just happen to be the best mathematical tool that
I have identified for finding hidden patterns and relationships in
seemingly disparate market data and making highly accurate short-
term market forecasts in a non-subjective, quantitative manner. Neural
networks are not a magic bullet. They are the means, not the end.
Neural Networks Learn Patterns and Make
Forecasts
Over the past decade since first appearing on the financial indus-
try scene, neural networks have been applied successfully to finan-
cial forecasting, corporate decision-making (including risk analysis
and fraud detection), character recognition and medical diagnostics,
to name a few application areas.
Recently with prominent software companies developing and pro-
moting neural network software for decision analysis such as Com-
puter Associates International’s Neugents
™
software, neural networks
have become more accepted as a mainstream mathematical tool.
The Input Layer
A neural network is not limited to single-market technical data
inputs. A neural network is excellent at applying intermarket data (as
well as fundamental data) to market forecasting.
For instance, for a neural network designed to forecast New York
Light Crude Oil, the analysis includes ten years of past price, volume
and open interest data on crude oil futures.
The analysis also includes the following intermarket inputs: crude
oil cash, the Bridge/CRB Futures Price Index, the S&P 100, Comex
gold, Comex silver, the Japanese yen, N.Y. heating oil #2, Treasury
bonds and the U.S. Dollar Index. Additionally, fundamental data in-
puts can be incorporated. Once the raw input data has been select-
ed, it is preprocessed using various algebraic and statistical methods
of transformation, in order to facilitate learning.
Trend Forecasting With Technical Analysis 95
96 Trade Secrets
The Hidden Layer
The hidden layer is used by a neural network for internal process-
ing to store its “intelligence” during the learning process. This layer is
composed of neurons where the network recodes the input data into
a form that captures hidden patterns and relationships. The network
generalizes from previously learned facts to new inputs, which allows
it to make its forecasts. The number of neurons in the hidden layer
and the number of hidden layers are determined through experi-
mentation.
The Output Layer
The output layer is where a network’s forecasts are made. Two
types of real number outputs in financial analysis include forecasts of
prices such as the next day’s high and low, and forecasts of technical
indicators such as a predicted 5-day moving average value for two
days in the future. Decisions must be made about not only what out-
put to forecast, but also how far into the future to make the forecast.
Learning Algorithms
There are many different learning algorithms that can be used to
train a neural network. Each algorithm has different performance
characteristics. All of the algorithms attempt to minimize the overall
error in the network’s forecasts.
One popular learning algorithm is the gradient-descent algorithm.
However, gradient-descent trains slowly and often finds sub-optimal
solutions. This limitation is similar to pitfalls encountered with back-
testing and optimization of rule-based trading strategies in which sub-
optimal sets of parameter values are found that are isolated and
unstable.
How a Neural Network Learns
Training a neural network involves a repetitive mathematical
process in which the neural network learns underlying hidden pat-
terns, discerns leads and lags and identifies nonlinear relationships
within the data from repeated exposures to the input data. Learned
information is stored by the network in the form of a weight matrix,
with changes in the weights occurring as the network “learns.” Similar
to the learning process people engage in, a neural network learns
patterns by being exposed to repeated examples of them. Then the
neural network generalizes through the learning process to related
but previously unseen patterns.
One popular network paradigm that has been used for financial
market analysis and forecasting is known as a “feed-forward” network
that trains through “back-propagation of error” which is depicted in
Figure 6-2.
Once trained, a neural network acts as a market forecasting tool,
allowing traders to achieve the trend identification and forecasting
goals of technical analysis.
Trend Forecasting With Technical Analysis 97
FIGURE 6-2. SIMPLE FEED-FORWARD BACK-PROPAGATION NEURAL NETWORK
Source: Market Technologies Corporation
A simple feed-forward back-propagation network, using technical and intermarket
data as inputs, trains by back-propagation of error throughout the network.
Trend Forecasts
Back
Propagation
of Error Output
Hidden
Input
Input Data From Target Market and
Related Markets
98 Trade Secrets
Overtraining Is Not Desirable
Overtraining a neural network must be avoided. Overtraining
occurs when a neural network memorizes the subtleties and idio-
syncrasies particular to specific training data, without developing the
capacity to generalize to new data. Overtraining is analogous to
curve-fitting or over-optimization when performing back-testing and
optimization on rule-based trading strategies. An overtrained network
will perform poorly on out-of-sample test data and subsequently
when making its forecasts during realtime trading.
How a Neural Network Is Tested for Accuracy
Testing is performed by creating an independent test file made up
of data that had not been seen by a neural network during the train-
ing process. In the testing mode the neural network is given these
new inputs and utilizes the representation that it had previously
learned to generate its forecasts. This allows the network to be eval-
uated under simulated trading conditions. This is analogous to “walk-
forward” or “out-of-sample” testing of rule-based trading strategies.
Performance results from various neural networks on test data can
be compared prior to making a determination about which specific
neural network to select for use in the final application. Depending
on the comparative test performance results, changes often need to
be made in the selection of input data, preprocessing, network archi-
tecture, etc., and retraining conducted before the final application
network is selected.
There’s More to Neural Networks
There are similarities and differences between designing and train-
ing a neural network and developing and testing rule-based trading
strategies. If you want to learn more about the technical details and
underlying mathematics behind neural networks, I refer you to my
personal website www.FutureForecasts.com which includes reprints
of many of the research articles and book chapters I have previous-
ly written about the application of neural networks to technical analy-
sis and market forecasting.
THE NEXT HORIZON
Where Do We Go From Here and
What Does This Mean for Traders?
A
s the world’s financial markets become increasingly integrat-
ed, intermarket analysis will play a crucial role in market
analysis in the first decades of the 21st century, just as back-
testing and optimization of single-market trading strategies became
integral to computerized technical analysis in the late 20th century.
The narrow single-market approach that analyzes each individual
market based upon its own internal past price data must be sup-
planted by a multi-dimensional approach. A decade ago I referred
to the synthesis of technical, intermarket and fundamental ap-
proaches as “synergistic market analysis.” No financial market is an
island. They are now all integrally linked to one another.
Fortunately, neural networks are not only well-suited to analyzing
markets from both a single-market as well as an intermarket per-
spective, but can also incorporate fundamental data inputs. These
might include supply and demand statistics, and economic data
such as the Gross National Product, the Producer Price Index, the
Consumer Price Index and Unemployment statistics. Even compar-
ative economic statistics from different countries can be included.
In effect, as the financial markets continue to evolve, technical
analysis, intermarket analysis and fundamental analysis will blend
together, creating the three-legged stool known as financial market
analysis.
By utilizing the computational modeling capabilities of neural net-
works in a structured framework that integrates seemingly disparate
Trend Forecasting With Technical Analysis 99
Chapter 7
100 Trade Secrets
technical, intermarket and
fundamental data as depict-
ed in Figure 7-1, quantita-
tive trend forecasting will
continue to be at the cut-
ting-edge of financial market
analysis in the 21st century.
History is replete with ac-
counts of newly emerging
technologies, which have
subsequently had a major
impact on economic devel-
opment and the financial
markets —making early a-
dopters wealthy in the
process. The railroad, the air-
plane, the telephone, xerog-
raphy, and the Internet rep-
resent such technologies,
with substantial commercial
applications, which have
become part of the econom-
ic landscape.
Technological progress cannot be forestalled by those who are skep-
tical, inflexible or simply too afraid to adopt something new or differ-
ent. Such close-mindedness and shortsightedness is an anachronism
in today’s rapidly changing technology-driven world.
Within the financial industry, the same can be said for the applica-
tion of advanced quantitative technologies such as neural networks
and intermarket analysis to global financial market analysis and trad-
ing. In the past, new analytical innovations involving the application
of quantitative technologies have met resistance within the financial
industry. In the future, though, as emerging technologies demonstrate
their effectiveness they will become more quickly incorporated into
the practice of financial market analysis.
Neural networks are real; they work, and they are here to stay. Still,
they are just one of the mathematical tools applicable to the imple-
mentation of synergistic trading strategies. Other tools, including ex-
pert systems, genetic algorithms, fractal geometry, chaos theory and
FIGURE 7-1. SYNERGISTIC ANALYSIS
LOOKS AT THE BIG PICTURE
Source: Market Technologies Corporation
The next phase in the evolution of technical
market analysis will be “synergistic market
analysis,” combining technical, intermar-
ket and fundamental data. This completes
the three-legged stool of financial market
analysis, covering the entire global eco-
nomic and financial landscape.
Technical
Data
Fundamental
Data
Intermarket
Data
fuzzy logic to name a few, are also being applied to market analysis
with varying degrees of success. There is certainly much more to
come!
There Will Never Be a Financial Crystal Ball
My research and development efforts will continue to be focused
on increasing VantagePoint’s forecasting accuracy. Some of the factors
that are under study involve the inclusion of additional global mar-
kets to be considered as intermarket inputs and the optimization of
the size of the moving average lengths and look-forward periods that
are used to make the trend forecasts.
In addition, I intend to develop additional VantagePoint programs
to monitor financial markets outside of the United States such as
Short Sterling on the London International Financial Futures Ex-
change and the Euroyen on the Singapore Exchange Ltd. I am also
interested in applying intermarket analysis to individual large-cap
equities comprising the Nasdaq-100 Index and assessing the impact
of incorporating fundamental data inputs into VantagePoint.
Obviously, there will never be a financial crystal ball that traders
can gaze into to see what the markets will do in the future with 100%
accuracy. In my opinion it will not be possible for market analysts to
predict trend direction with more than 80-85% accuracy, due to ran-
domness and unpredictable events that are inherent in the global
financial markets, as well as the difficulty of developing effective fore-
casting tools.
With VantagePoint’s current accuracy level over 70% on all twenty-
five markets monitored, over 75% on fourteen of them, and over 80%
on two of them (the 5-year Treasury notes and gas oil), VantagePoint
is already within striking distance of what is realistically attainable in
terms of forecasting accuracy.
Even then, there are a myriad of additional factors such as mass psy-
chology, judgment, trading experience, risk propensity, fear, greed,
money management and amount of capital that affect one’s trading
performance.
I am determined to push the forecasting envelope as far as it will
go. It’s my passion. This is what has made the financial markets and
Trend Forecasting With Technical Analysis 101
102 Trade Secrets
technical analysis so emotionally exciting, intellectually challenging
and financially compelling to me.
Right now, a robust, yet easy-to-use, intermarket analysis tool such
as VantagePoint is a smart way for serious traders to fill the gap in
their technical analysis arsenals so they can start benefiting immedi-
ately from intermarket analysis without having to reinvent the wheel
or study to become rocket scientists.
As more traders embrace intermarket analysis and incorporate it
into their trading, they will be able to make winning market trades
based on the hidden relationships and complex patterns between
related markets, reflecting the market synergy behind today’s global
markets.
I hope that this book has helped make you more aware of the
implications that the globalization of the financial markets has on
your own trading, and am confident that by broadening your per-
spective to include intermarket analysis, whether you are a stock,
options or futures trader, you will be able to improve your trading
performance and self-confidence to make more decisive and prof-
itable trading decisions.
If you have any questions concerning any of the information cov-
ered in this book, please feel free to contact Market Technologies
Corporation by e-mail at [email protected] or through its website
at www.ProfitTaker.com where you can learn more about intermarket
analysis, neural networks and VantagePoint.
At the website, you can also examine actual up-to-date Vantage-
Point Daily Reports for various financial markets, which will show
you in more detail how VantagePoint can benefit you. Additionally,
you can register on the website to receive free e-mail alerts from
Market Technologies Corporation. You can also contact Market Tech-
nologies Corporation by telephone at 800-732-5407 or 813-973-0496
or by fax at 813-973-2700.
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Guide
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112 Trade Secrets
Learn More About
VantagePoint Software
Trend Forecasting and Market Timing Technology
? ? ? ? ? ?
Discover how you can stack the odds in your
favor with VantagePoint Software—and its
amazing forecasting capabilities . . .
I
t is no longer sufficient for traders to focus internally on single-mar-
kets in isolation of what related markets are doing. A new aspect
of technical analysis, known as intermarket analysis, has become a
critical ingredient to successful trading. To be competitive, traders
must now have a broad intermarket perspective and the necessary
analysis tools to implement it. VantagePoint Intermarket Analysis Soft-
ware will give you a road-map—showing you what it expects the
market to do—thereby giving you the
self-confidence to take trades that should
be taken—and keep you out of margin-
al trades that should be avoided.
VantagePoint anticipates
trends —it does not
follow them!
VantagePoint was designed by traders
who understand that to be successful in
today’s markets, you need to have a
“heads up” on what is most likely to hap-
pen in each market tomorrow, not just
what it has done today or in the past!
With VantagePoint’s forecasting capabili-
VANTAGEPOINT:
• Monitors major
financial markets
• Five neural
networks make
independent
forecasts
• Reports offer
detailed analysis
on past and
future forecasts
• Intermarket
charts show you
what’s ahead
Trend Forecasting With Technical Analysis 113
ties, each day you’ll know—with
nearly 80% proven accuracy:
• What trend direction is anticipated
over the next two to four days
• Tomorrow’s expected high/low
• Whether the market is expected to
make a top or bottom
Plus . . . VantagePoint
is quick and easy to use
• VantagePoint is ready to use when
you receive it.
• You do NOT need to know anything
about intermarket analysis or neural
networks.
• You don’t even need to know anything
about programming. Unlike other com-
plicated software programs, VantagePoint is easy to use and lets
you focus on trading instead of getting distracted by the complex-
ities of the software itself.
• The Daily Update function within VantagePoint automatically pro-
cesses VantagePoint’s five neural networks, which then generate
their forecasts for the next day’s trading. All you do is compare the
Daily Reports (or charts) for several target markets to see which
markets offer the best trades to take the next day. The process
takes only a few minutes from start to finish.
What more do you need to be successful?
Discover the power of this amazing software program—and start
stacking the odds in your favor today. Call now for full details.
Call 800-732-5407
Extension 100
www.ProfitTaker.com/93110
BENEFITS:
• Pinpoints the
best trades
• How to get added
confirmation
• Day and position
trading with
tomorrow’s price
forecasts
• Stop placement
based on
forecasts not
hunches
• and more
TM
114 Trade Secrets
Industry Pros, Real Traders,
and Product Reviewers are Raving about
VantagePoint
? ? ? ? ? ?
“Louis Mendelsohn was the first person to develop intermarket analy-
sis software in the financial industry during the 1980s. He is the lead-
ing pioneer in the application of microcomputer software and neural
networks to intermarket analysis.”
— John Murphy, president of MurphyMorris.com
“I have known Lou Mendelsohn for years and am impressed by his
sincere desire to help traders improve their performance. His no non-
sense approach to research and trading makes VantagePoint an ex-
tremely useful tool to evaluate and trade the markets.”
— Walter Bressert, Author, Technical Analyst, CTA
“I have bought many trading programs but none match the versatility
or adaptability of VantagePoint. The daily report is simple to under-
stand and implement, a joy to use for position or day trading. The pre-
dicted high and low for the next day’s trading astounds me with its
amazing accuracy.” — Jim Drysdale, VantagePoint Client
“VantagePoint allows me to select when to trade and when to stay out
of bad market conditions. Having multiple VantagePoint reports lets
me pick the one or two markets with the strongest indicators. A pru-
dent trader should be able to recoup the cost of the software in a fair-
ly short period of time.” — Ralph Hanahan, VantagePoint Client
“Any user who adheres to the advice in the manuals should quickly
recoup their outlay. Highly recommended.” — Investor’s Chronicle
“The end result will clearly be its ability to make profits for the
trader.” — Jake Bernstein’s Commodity Trading Letter
Learn more about this amazing software.
Call 800-732-5407
Extension 100
www.ProfitTaker.com/93110
TM
Trend Forecasting With Technical Analysis 115
About the Author and
Market Technologies
Corporation
? ? ? ? ? ?
Louis B. Mendelsohn is president and chief executive officer of
Market Technologies Corporation. Mr. Mendelsohn began trading
equities in the early 1970s, followed by stock options. Then, in the late
1970s he started trading commodities, as both a day and position trad-
er. In 1979, he formed Market Technologies Corporation to develop
technical analysis trading software for the commodity futures markets.
In 1983, Mendelsohn pioneered the first commercial strategy back-
testing and optimization trading software for microcomputers. By the
mid-1980s these capabilities became the standard in microcomputer
trading software for both equities and futures, fueling the growth of
today’s multi-million dollar technical analysis software industry.
Recognizing the emerging trend toward globalization of the
world’s financial markets, in 1986 Mr. Mendelsohn again broke new
ground in technical analysis when he introduced the first commer-
cial intermarket analysis software in the financial industry for micro-
computers.
Building on his extensive research in the 1980s involving intermar-
ket analysis, in 1991 Mendelsohn released VantagePoint Intermarket
Analysis Software, which makes short-term market forecasts based
upon the pattern recognition capabilities of neural networks. Since
then, Mendelsohn’s research has continued to focus on intermarket
analysis and market forecasting. In addition to his research, software
development and corporate management responsibilities, he actively
trades in the financial markets.
Mr. Mendelsohn has written extensively since 1983 in many promi-
nent financial publications including Barron’s
®
, Futures, and
Technical Analysis of Stocks & Commodities
™
. He has been widely
quoted in the financial media including The Wall Street Journal and
Investor’s Business Daily, has collaborated on more than half a
dozen books on technical analysis, and has been interviewed live on
national radio and television, including CNBC.
Mendelsohn has also spoken at numerous financial conferences
and symposia, including the Futures Industry Association annual
meeting, Futures Symposium International, the Harvard Business
School Alumni Club, Futures Truth and the Annual Meeting of the
Association for Investment Management and Research.
Due to his achievements in the application of computers and
information technologies to technical analysis over the past quarter-
century, his biography is included in Marquis Who’s Who in the
World
®
, Who’s Who in America
®
, and Who’s Who in Finance and In-
dustry
®
. He has been a full member of the Market Technicians Asso-
ciation since 1988, and is a colleague of the International Federation
of Technical Analysts.
Born in 1948 in Providence, Rhode Island, Mendelsohn received a
B.S. degree in Administration and Management Science from
Carnegie Mellon University in 1969, an M.S.W. degree from the State
University of New York at Buffalo in 1973, and an M.B.A. degree
with Honors from Boston University in 1977.
Since its founding by Mr. Mendelsohn, Market Technologies Cor-
poration has been at the forefront of development of state-of-the-art
technical analysis tools and information technologies for the finan-
cial markets. Located in the Tampa Bay region of Florida since 1979,
the firm has individual and institutional clients in over thirty coun-
tries throughout the world.
Market Technologies Corporation was recently ranked the 29th
fastest growing private corporation in Florida, out of the top one-hun-
dred companies in the Florida 100 competition based on three-year
revenue growth, sponsored by the University of Florida, Deloitte &
Touche LLP, PricewaterhouseCoopers LLP, and Raymond James &
Associates, Inc.
116 Trade Secrets
Trend Forecasting With Technical Analysis 117
Market Technologies Corporation was also ranked the 17th fastest
growing technology company in Tampa Bay, based on five-year rev-
enue growth, out of the top fifty public and private technology firms
in the Tampa Bay Technology Fast 50 competition, sponsored by
Deloitte & Touche LLP.
COMPANY INFORMATION:
Market Technologies Corporation
E-mail address: [email protected]
Website address: www.ProfitTaker.com
Phone: 800-732-5407 or 813-973-0496
Fax: 813-973-2700
25941 Apple Blossom Lane
Wesley Chapel, Florida 33544
Free 2 Week Trial Offer for
U.S. Residents From
Investor’s Business Daily:
I
NVESTOR’S BUSINESS DAILY will provide you with the
facts, figures, and objective news analysis you need
to succeed.
Investor’s Business Daily is formatted for a quick and
concise read to help you make informed and profitable
decisions.
To take advantage of this free 2 week trial offer,
e-mail us at [email protected]
or visit our website at www.traderslibrary.com
where you find other free offers as well.
You can also reach us by calling 1-800-272-2855
or fax us at 410-964-0027.
F
R
E
E
2
W
E
E
K
T
r
i
a
l
O
f
f
e
r
Trend Forecasting With Technical Analysis 119
This book, along
with other books,
are available at discounts
that make it realistic to provide them
as gifts to your customers, clients,
and staff. For more information on
these long lasting, cost effective pre-
miums, please call John Boyer at
800-424-4550 or e-mail him at
[email protected]
Market techniques that worked in the last century won’t work in the cur-
rent one. Now, Louis Mendelsohn’s groundbreaking book takes technical
analysis to the next level —giving today’s traders all the tools needed to
make more winning trades —more often.
Mendelsohn presents a comprehensive approach—combining
technical and intermarket analysis into one powerful framework for
accurately forecasting trends.
You’ll also discover . . .
• Precise trading strategies that can be used by both
day traders and position traders
• The limitations of traditional technical analysis methods
• How to use moving averages as a leading—not lagging—indicator
by the application of neural networks to intermarket analysis
PLUS —an introduction to VantagePoint Software, and its amazing fore-
casting capabilities. This powerful software makes Mendelsohn’s “new
economy”trading methods
work simply—and effectively.
“
Since I was the one who first described inter-
market principles 10 years ago, I feel indebted to
Mendelsohn for proving that those ideas do, in
fact, work and can be profitably applied to the
financial markets.
”
— JOHN MURPHY, President, MurphyMorris.com
$19.95 US
Marketplace Books
P.O. BOX 2466
Ellicott City MD 21041
doc_580077252.pdf
The globalization of the financial markets and outlines some of the major factors that are responsible for the emergence of the global economy.
Trend
Forecasting
With
Technical
Analysis
Trend
Forecasting
With
Technical
Analysis
UNLEASHING THE HIDDEN POWER OF INTERMARKET
ANALYSIS TO BEAT THE MARKET
LOUIS B. MENDELSOHN
FORWORD BY JOHN J. MURPHY
T R A D E S E C R E T S
Trend
Forecasting
With Technical
Analysis
Unleashing the Hidden Power
of Intermarket Analysis
to Beat the Market
BY LOUI S B. ME NDE L S OHN
Foreword by
John J. Murphy
Titles in the
Trade Secrets Series
Trend Forecasting With Technical Analysis:
Unleashing the Hidden Power of
Intermarket Analysis to Beat the Market
by Louis B. Mendelsohn
7 Chart Patterns That Consistently Make
Money by Ed Downs
Charting Made Easy by John Murphy
The Four Biggest Mistakes in Futures Trading
by Jay Kaeppel
The Four Biggest Mistakes in Options Trading
by Jay Kaeppel
Bar Chart Basics by Darrell Jobman
Trading System Secrets: Selecting a Winning
System by Joe Krutsinger
Profit Strategies: Unlocking Trading
Performance with Money Management
by David Stendahl
Simple Asset Allocation Strategies
by Roger Gibson
“Intermarket analysis tools —that build and
expand upon the single-market analysis methods
which defined technical analysis in the late
20th century —demand serious attention.”
— Louis B. Mendelsohn
Copyright © 2000 Market Technologies Corporation
Published by Marketplace Books
All rights reserved.
“VantagePoint Intermarket Analysis Software,” “Market Technologies Corporation” and “ProfitTaker” are
trademarks of Market Technologies Corporation. “Synergistic Market Analysis,” “Synergistic Analysis” and
“Market Synergy” are trademarks of Louis B. Mendelsohn. “Investor’s Business Daily” is a registered trade-
mark of Investor’s Business Daily, Inc. “Technical Analysis of Stocks & Commodities” is a trademark of
Technical Analysis, Inc. “Standard & Poor’s 500” is a trademark of The McGraw-Hill Companies, Inc. “S&P
500” and “S&P 100” are registered trademarks of The McGraw-Hill Companies, Inc. “Nikkei Stock Average”
and “Nikkei” are registered trademarks of Nihon Keizai Shimbun Inc. “CNBC” is a trademark of National
Broadcasting Company, Inc. “CNN” is a trademark of Cable News Network LP, LLLP, a Time Warner
Company. The “Nasdaq-100 Index,” “Nasdaq-100,” “Nasdaq Composite” and “Nasdaq” are registered trade-
marks of The Nasdaq Stock Market, Inc. “Nasdaq Japan” is a service mark of The Nasdaq Stock Market, Inc.
“Futures” is a registered trademark of Futures Magazine Inc.
“The New York Stock Exchange” and “NYSE Composite Index” are registered trademarks of the New York
Stock Exchange, Inc. Global Equity Market is a trademark of the New York Stock Exchange, Inc.
“TradeStation” is a registered trademark of Omega Research, Inc. “Who’s Who in America,” “Who’s Who in
the World” and “Who’s Who in Finance and Industry” are registered trademarks of Reed Publishing
(Nederland) B.V. Licensed to Reed Elsevier Inc. “The Wall Street Journal” and “Barron’s” are registered trade-
marks of Dow Jones & Company, Inc. “The Dow,” “Dow Jones Industrial Average” and “Dow Jones Utility
Average” are service marks of Dow Jones & Company, Inc. “Bridge/CRB” is a registered trademark of
Bridge/Commodity Research Bureau, a division of Bridge Information Systems Inc. The FTSE 100 index is
calculated by FTSE International Limited (FTSE). “FTSE” is a trade and service mark of London Stock
Exchange Limited and The Financial Times Limited and is used by FTSE under licence. FTSE accepts no
liablity for any loss or damage arising from the use of the FTSE 100 index. CBOT is a registered trademark
of the Board of Trade of the City of Chicago. Amtrak is a registered trademark of the National Railroad
Passenger Corporation. Neugents is a trademark of Computer Associates International, Inc. All other trade-
marks, service marks or registered trademarks referred to in this publication are the property of their respec-
tive owners. Other names, designs, titles, words, logos or phrases in this publication may constitute trade-
marks, service marks or trade names of other entities which may be registered in certain jurisdictions.
The elephant is Digital Imagery © copyright 2000 PhotoDisc, Inc.
Reproduction or translation of any part of this work beyond that permitted by Section 107 or 108 of the
1976 United States Copyright Act without the permission of the copyright owner is unlawful. Requests for
permission or further information should be addressed to the Permissions Department at Traders’ Library.
This publication is designed to provide accurate and authoritative information and the views and opinions
of the author in regard to the subject matter covered. It is sold with the understanding that neither the pub-
lisher, copyright holder, nor the author is engaged in (i) providing commodity trading advice based on, or
tailored to, the commodity interests or cash market positions or other circumstances or characteristics of any
particular client, or (ii) rendering investment, legal, accounting or other professional services. If trading or
investment advice or other expert assistance is required, the services of a competent and appropriately
licensed person should be sought.
From a Declaration of Principles jointly adopted by a Committee of the
American Bar Association and a Committee of Publishers.
ISBN 1-883272-91-2
Printed in the United States of America.
This book, along with other books, are available at discounts that
make it realistic to provide them as gifts to your customers, clients
and staff. For more information on these long-lasting, cost-effective
premiums, please call John Boyer at 800-424-4550 or e-mail him at
[email protected].
Contents
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Chapter 1
TRADING IN THE GLOBAL ECONOMY— Have Your
Trading Strategies and Profits Kept Pace? . . . . . . . . . . . . . . . . . . 25
The Markets Are Constantly Evolving . . . . . . . . . . . . . . . . . . . 26
The World’s Futures and Equity Markets Are Linked . . . . . . . . 27
Emerging Forces Usher in the New Global Economy. . . . . . . . 29
Market Volatility and Financial Crises Are Here to Stay. . . . . . . 31
Chapter 2
SINGLE-MARKET ANALYSIS—Trading With Tunnel Vision
Can Put You on the Losing Side of a Trade . . . . . . . . . . . . . . . . 35
While Numbers Don’t Lie, They Can Be Deceiving . . . . . . . . . 36
The Goal Is to Forecast Market Trend Direction . . . . . . . . . . . 36
You Can Play the Markets, or You Can Time the Markets . . . . . 37
Technical Analysis Has Not Kept Pace With the Markets. . . . . . 38
Traders Need to Take Off Their Blinders. . . . . . . . . . . . . . . . . 41
Chapter 3
INTERMARKET ANALYSIS—Seizing Trading Opportunities in a
Shrinking World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Intermarket Analysis in the Equity and Commodity Markets . . . 46
No Market Is Exempt From Globalization . . . . . . . . . . . . . . . 49
7
Why Markets Converge or Diverge . . . . . . . . . . . . . . . . . . . . 50
Intermarket Dynamics Must Be Taken Into Consideration . . . . 51
Early Attempts at Intermarket Analysis Fall Short . . . . . . . . . . 51
Tracking Related Markets Pays Off . . . . . . . . . . . . . . . . . . . . 52
Full Field of Vision Is Critical . . . . . . . . . . . . . . . . . . . . . . . . 53
Intermarket Analysis: In the Right Place at the Right Time. . . . 56
The Only Thing Certain Is Uncertainty Itself . . . . . . . . . . . . . 57
Chapter 4
TODAY’S MARKETS HAVE CHANGED—Why Trend Forecasting
Beats Trend Following and How Traders Can Profit. . . . . . . . . . 59
Moving Averages Are Lagging Indicators. . . . . . . . . . . . . . . . . 60
Moving Averages Are Popular —But Something’s Missing. . . . . 62
Moving Average Crossovers Lead to Whipsaws . . . . . . . . . . . . 63
Computing a Simple Moving Average Is Easy . . . . . . . . . . . . . 65
Displaced Moving Averages: Close But “No Cigar” . . . . . . . . . . 66
A New Way to Forecast Moving Averages . . . . . . . . . . . . . . . . 66
Leading Indicators Give You a Competitive Edge. . . . . . . . . . . 69
Chapter 5
VANTAGEPOINT FORECASTS MARKET DIRECTION—
How to Get a Sneak Preview of Where the Markets Are
Going and Use This Information to Your Advantage . . . . . . . . . 71
VantagePoint Monitors Major Financial Markets . . . . . . . . . . . . 71
Five Neural Networks Make Independent Forecasts . . . . . . . . . 73
What VantagePoint’s Daily Report Tells You . . . . . . . . . . . . . . 76
Intermarket Charts Show You What’s Ahead . . . . . . . . . . . . . 80
VantagePoint Is Quick and Easy . . . . . . . . . . . . . . . . . . . . . . 82
How to Find a Good Trade . . . . . . . . . . . . . . . . . . . . . . . . . 83
Here’s How to Get Added Confirmation . . . . . . . . . . . . . . . . 84
Day and Position Trading With Tomorrow’s Price Forecasts . . . 88
Stop Placement Based on Forecasts Not Hunches. . . . . . . . . . 89
Other Markets Give Added Confirmation . . . . . . . . . . . . . . . . 90
How To “Cherry-Pick” the Best Trades to Take. . . . . . . . . . . . 91
8
Chapter 6
NEURAL NETWORKS—How to Raise Your Financial IQ
to Stay Ahead of the Competition . . . . . . . . . . . . . . . . . . . . . . . 93
Neural Networks Combine Technical and Intermarket Data . . . 94
Neural Networks Learn Patterns and Make Forecasts . . . . . . . . 95
Chapter 7
THE NEXT HORIZON—Where Do We Go From Here
and What Does This Mean for Traders? . . . . . . . . . . . . . . . . . . 99
There Will Never Be a Financial Crystal Ball . . . . . . . . . . . . . 101
Trading Resource Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
About the Author and Market Technologies Corporation . . . . . . . . 115
9
Foreword
T
hey say timing is everything. Nowhere is that more true than
in the financial markets. It’s especially timely that Lou
Mendelsohn’s book on intermarket analysis should appear at
the start of the new millennium. At the start of the last decade, I pub-
lished a book on the same topic—Intermarket Technical Analysis:
Trading Strategies for the Global Stock, Bond, Commodity, and Cur-
rency Markets (John Wiley & Sons, 1991). At that time, the principles
of intermarket analysis seemed heretical by suggesting that single-
market analysis (that had been utilized for the past century by mar-
ket technicians) was no longer adequate. By the end of the decade,
those seemingly radical ideas had become so accepted that the
Market Technicians Association listed intermarket analysis as a branch
of technical analysis.
It’s hard, for example, for any market analyst who lived through the
Asian crisis of 1997 to dispute the existence of global linkages —and
the interdependence of all financial markets. The collapse of one
Asian currency in the summer of that year caused a domino effect
throughout all of Asia. Before long, Asian bankers were raising inter-
est rates to stem the spreading currency collapse. That had a devas-
tating effect on the Asian stock markets. That deflationary threat
pushed global commodities into a free-fall and caused a massive rota-
tion out of global stocks into U.S. Treasury bonds.
It’s equally hard to argue with how the tripling of oil prices during
1999 pushed global interest rates higher and caused a bear market in
bonds. That prompted the Federal Reserve Board to start raising inter-
est rates in the middle of that year. A series of Fed tightenings over
the next twelve months had a predictably restraining effect on the
bull market in stocks. The impact of rising oil prices (and rising inter-
est rates) could also be seen in sector rotations within the stock mar-
ket. While rising oil prices were bullish for the energy sector during
Trend Forecasting With Technical Analysis 11
1999, they had a predictably bearish impact on interest-rate sectors of
the stock market (like financial stocks and utilities) and oil-sensitive
groups like the airlines. By the middle of the year 2000, economists
who had ignored the surging oil market during 1999 were crediting
that surge with slowing down the U.S. economy.
In case anyone wasn’t convinced a decade ago, market events
since then have amply demonstrated that all markets are linked—
and that a thorough market analysis has to take these intermarket
relationships into consideration. Lou Mendelsohn’s book takes those
intermarket ideas to an even more practical level. As he correctly
points out, the problem with intermarket relationships is that there
are so many of them. One of his intermarket trading models incor-
porates as many as nine related markets. With so many markets inter-
acting at the same time, it has become increasingly difficult for the
human mind to make sense of it all. Enter neural networks.
One of Mendelsohn’s greatest contributions to intermarket analysis
has been his application of neural networks to the process. He shows
how a neural network can take any number of related factors into
consideration, analyze them, and draw some practical conclusions.
And, those conclusions lead to the real benefit —winning market
trades. The results of two decades of pioneering work has produced
highly successful intermarket trading programs. Since I was the one
who first described these intermarket principles ten years ago, I feel
indebted to Mendelsohn for proving that those ideas do in fact work
and that they can be profitably applied to the financial markets.
Neural networks even incorporate fundamental factors into techni-
cal and intermarket work. When talking about things like inflation
and interest rates, the technical analyst sounds more like an econo-
mist than a chartist. Mendelsohn incorporates intermarket, funda-
mental, and technical considerations into an approach that he calls
“synergistic market analysis” —a term I first heard him use when I
interviewed him on CNBC
™
. For some purists, that may be a prob-
lem. For the rest of us, it’s just another step in the evolution of tech-
nical analysis. Intermarket work has a tendency to blend the funda-
mental and the technical —a trend that I expect to accelerate in the
new millennium. And I suspect that many of the techniques
described by Mendelsohn in this pioneering work will play an impor-
tant role in helping to bring about those changes.
12 Trade Secrets
Mendelsohn warns that what worked for technical analysts in the
old century may not work in the new one. Many of us started out
using pencils and rulers. We graduated to hand-held calculators be-
fore switching over to computers. Now comes neural networks.
Different times demand different tools. An increasingly interdepen-
dent financial marketplace will demand an even better set of tools.
It will also demand a more comprehensive approach to market
analysis that incorporates all geographic regions and all markets —
in other words, an intermarket approach.
—John Murphy
? ? ? ? ? ?
Mr. Murphy is also the author of Technical Analysis of the
Financial Markets and The Visual Investor and is the presi-
dent of MurphyMorris.com.
Trend Forecasting With Technical Analysis 13
Preface
T
his book explores the application of intermarket analysis,
which analyzes the relationships between financial markets
and their influences on each other. It examines the critical role
that intermarket analysis plays in assisting traders to identify and antic-
ipate changes in market direction in today’s globally interconnected
financial markets.
These markets include stock indexes such as the Dow Jones Indus-
trial Average
SM
, London’s FTSE
™
100 Index, the Nasdaq Composite
®
Index, the Nasdaq-100 Index
®
, the Nikkei Stock Average
®
(Japan) and
the Standard & Poor’s 500
™
Stock Index; currencies such as the British
pound, Japanese yen, Swiss franc and the U.S. Dollar Index; energy
markets such as crude oil, gasoline and heating oil; interest rate mar-
kets such as the eurodollar, Treasury bonds and Treasury notes; as
well as individual equities.
As the burgeoning global economy of the 21st century, fostered by
advancements in information technologies, contributes to the further
integration of the financial markets, intermarket analysis will become
an integral part of the overall field of technical analysis. Intermarket
analysis empowers traders to make more effective trading decisions
based upon the linkages between related financial markets. By incor-
porating intermarket analysis into your trading strategies, rather than
limiting your scope of analysis to each individual market, these rela-
tionships and interconnections between markets will work for you
rather than against you.
Suggestions are made for how intermarket analysis can be used in
conjunction with traditional single-market technical indicators to pro-
vide a more comprehensive framework of analysis and broadened
trading perspective. This book also introduces VantagePoint Intermar-
ket Analysis Software which has achieved an astounding accuracy
rate of nearly 80% at forecasting market direction, and offers insights
Trend Forecasting With Technical Analysis 15
16 Trade Secrets
into how day traders and position traders in both the futures and
equity markets can use this powerful analysis tool to improve their
trading performance and achieve a competitive advantage over other
traders.
This book will be of interest to both experienced individual and
professional traders as well as newcomers to the financial markets
who want to create wealth in today’s global markets.
Introduction
A
fter trading stocks and options for nearly a decade using var-
ious technical analysis methods, in the late 1970s, with en-
couragement from a physician friend who traded gold futures,
I started to both day trade and position trade commodities while
working professionally as a hospital administrator.
At first I subscribed to chart services, which had to be updated by
hand during the week. I often joked to my wife about having to
sharpen my #2 lead pencil so often, since the dullness of its point
affected how my support and resistance lines were drawn, which in
turn determined where I placed my stops. This was very annoying to
me whenever I anticipated the market direction correctly only to miss
out on a big move after being stopped out prematurely at a loss due
to an ill-placed stop.
Using a hand-held calculator to compute technical indicators in the
days before microcomputers, I learned the underlying theories and
mathematical equations for various indicators such as moving aver-
ages, and devised mathematical shortcuts to expedite my daily cal-
culations.
I was quite excited when I purchased my first microcomputer in
the late 1970s. Before long I was teaching myself programming and
writing simple software programs to automate many of these calcu-
lations.
I quickly realized that the marriage of microcomputers with tech-
nical analysis would revolutionize financial market analysis. While I
had been hooked on trading and technical analysis since the early
1970s, it was the decision to apply computers to technical analysis
that changed my life.
In 1979, at thirty-one years old, intent on pursuing this goal, I
formed Market Technologies Corporation. A year later, with my wife
Illyce’s support, I left the health-care industry to devote my full atten-
Trend Forecasting With Technical Analysis 17
18 Trade Secrets
tion to commodity trading, technical analysis and trading software de-
velopment.
My intent was to design technical analysis software that would do
more than just automate and speed up calculations I had been doing
by hand each evening with a calculator. I wanted to be able to cre-
ate and back-test various trading strategies to identify and forecast the
market direction of the commodity markets that I traded.
In 1983, I released ProfitTaker, the first commercially available
microcomputer trading software to perform strategy back-testing and
optimization. With its automated back-testing capabilities, ProfitTaker
represented a milestone in the evolution of computerized technical
analysis.
That same year I authored a series of articles in Futures
®
magazine.
In these articles I introduced the concepts of back-testing and opti-
mization for microcomputers and discussed the impact that these
innovations would have on technical analysis and trading.
Throughout the 1980s, I continued to develop more powerful trad-
ing software. I also wrote articles and collaborated on books on trad-
ing, in which I discussed the dangers of curve-fitting and over-opti-
mization in trading strategy back-testing. Additionally, I spoke about
these pitfalls in national television, radio, and magazine interviews
and at financial industry conferences as an invited speaker. Before
long, strategy development and back-testing had attracted the atten-
tion of traders around the world who were purchasing microcom-
puters for the first time.
While there was resistance from a few professionals in the finan-
cial industry whose own software had been rendered obsolete by
back-testing and optimization or who felt threatened by these inno-
vations in computerized technical analysis, I received encouragement
at the time from a number of prominent technicians and traders.
These included Darrell Jobman, who was editor-in-chief of Futures
magazine, as well as Larry Williams and Jake Bernstein, who were
early supporters of mine—and to whom I am grateful.
Several ProfitTaker clients subsequently became software develop-
ers themselves, and promoted competitive software programs emu-
lating ProfitTaker’s back-testing and optimization capabilities. Other
existing software developers, likewise, later introduced their own ver-
sions of back-testing software, including Omega Research’s Trade-
Station
®
in 1991.
Today back-testing and optimization are so integral to single-mar-
ket technical analysis that traders take these capabilities for granted.
I find it somewhat amusing when I hear new traders just learning
about technical analysis tell me that back-testing has always been in
trading software—as if automobiles have always existed.
By the mid-1980s, through my technical research and observations
on the markets, it had become apparent to me that single-market
technical analysis methods would no longer be sufficient. Given the
changes that were occurring in the financial markets due to advance-
ments in computing and telecommunications technologies and the
emerging “global economy,” I realized that such methods which look
internally at only one market at a time (and typically lag behind the
market) were too limited.
In 1986, while searching for a way to broaden the scope of tech-
nical analysis, I developed the first commercially available intermar-
ket analysis software for microcomputers. This program addressed
market interdependencies by using a spreadsheet format to correlate
movements in related markets, as well as expectations of economic
statistics, with the anticipated trend direction of a target market.
The global stock market crash of October 1987 starkly affirmed my
convictions about the interdependencies of the world’s futures, equi-
ty and derivative markets. At that point, I was convinced that inter-
market analysis would become an essential part of technical analysis
as the world economies and financial markets continued to become
more intertwined.
Despite my accomplishments at developing intermarket analysis
software, I was not satisfied with the mathematical tools I had used
to correlate market data from related markets. Then in the late 1980s
after experimenting with an artificial intelligence technology known
as neural networks, I concluded that they were ideally suited to the
tasks of finding repetitive patterns and nonlinear relationships
between a target market and related markets, and accurately fore-
casting market direction of the target market.
In 1991, after considerable research and development involving the
application of neural networks to financial forecasting, I introduced my
most advanced software program—VantagePoint Intermarket Analy-
Trend Forecasting With Technical Analysis 19
20 Trade Secrets
sis Software. VantagePoint uses neural networks to make short-term
forecasts of the market direction and prices of various financial
markets.
Around this same time, other technicians, including John Murphy,
the technical analyst for CNBC, working independently, were also ex-
ploring intermarket relationships, primarily from an intuitive and
descriptive standpoint. Their work lent further credibility among
traders to the new arena of intermarket analysis.
Since the late 1980s, I have written extensively in articles and books
about globalization and the integration of the world’s financial mar-
kets. During this time I have continued my research and software
development involving intermarket analysis, creating powerful trend
forecasting trading strategies built around predicted moving averages.
The technical focus of this book’s presentation is on how inter-
market analysis, through the application of neural networks, can be
used to forecast moving averages, making them a leading rather than
a lagging technical indicator.
• Chapter 1 discusses the globalization of the financial markets and
outlines some of the major factors that are responsible for the
emergence of the global economy.
• Chapter 2 highlights the limitations of traditional technical analy-
sis methods, particularly the emphasis on single-market analysis
and the reliance upon lagging trend-following indicators.
• Chapter 3 examines intermarket analysis as a logical extension of
technical analysis and offers various ways that intermarket analysis
can be used by traders to seize trading opportunities that other
traders miss.
• Chapter 4 explains the strengths and weaknesses of traditional mov-
ing averages, and shows how trend forecasting, by using neural net-
works applied to intermarket data, outperforms trend following.
• Chapter 5 describes VantagePoint’s market forecasting capabilities.
This chapter also presents various market timing trading strategies
utilizing predicted moving averages, which can be used by both
day traders and position traders.
• Chapter 6 looks at the application of neural networks to inter-
market analysis and briefly outlines the basics of neural networks
and how they can benefit traders in today’s global markets.
• Chapter 7 discusses the evolution of financial market analysis in
the first decades of the 21st century. It suggests a comprehensive
approach that I call “synergistic market analysis,” which combines
technical, intermarket and fundamental data into one framework
for the purpose of analysis and forecasting.
In summary, this book discusses the globalization of the world’s
financial markets and the application of intermarket analysis in devel-
oping and implementing powerful trend forecasting and market tim-
ing trading strategies in the equity, options, derivative and futures
markets.
Trend Forecasting With Technical Analysis 21
Trend
Forecasting
With Technical
Analysis
Unleashing the Hidden Power
of Intermarket Analysis
to Beat the Market
TRADING IN THE GLOBAL
ECONOMY
Have Your Trading Strategies
and Profits Kept Pace?
D
uring the last two decades of the 20th century, following the
advent of microcomputers, participation in the financial mar-
kets by individual traders has grown tremendously. Trading
software has proliferated as an increasing number of traders have em-
braced technical analysis methods for making trading decisions.
While microcomputers have become substantially faster and trad-
ing software has likewise undergone significant improvements in
speed, performance and user-friendliness, the overall success rate of
traders from a profitability standpoint has not materially improved.
The reason, in my opinion, is that the single-market emphasis of tech-
nical analysis has not kept pace with structural changes that have oc-
curred in the financial markets related to the emergence of the glob-
al economy.
Now, more than ever before, mass psychology and market senti-
ment seem to change daily, if not hourly, as market direction abrupt-
ly shifts from bullish to bearish and back again. One day a futures
market or individual stock is overbought, the next day it is oversold.
Today’s market darling is tomorrow’s ugly duckling. One day con-
cerns over inflation are of paramount importance to traders, the next
day the subject is practically forgotten as they move on to the next
hot topic. Fears over interest rates and “hard landings” wax and wane
as traders, with the attention span of hyperactive children, have diffi-
culty maintaining their focus, discipline and perspective.
Trend Forecasting With Technical Analysis 25
Chapter 1
26 Trade Secrets
To the novice, these sudden shifts between greed and fear, bull-
ishness and bearishness, optimism and pessimism, hope and resig-
nation, seem to exist in a vacuum without rhyme or reason. Yet pat-
terns of market behavior repeat themselves over and over again. They
can be found within each market, such as the Dow Jones Industrial
Average, at different periods in time, and from an intermarket per-
spective by analyzing relationships between related markets.
Domestic and foreign markets now, more often than not, move in
concert, driven by common financial, political and economic forces
affecting the global economy.
Today’s traders can no longer rely solely upon single-market tech-
nical analysis methods, which were designed for the more indepen-
dent and less volatile domestic markets of the late 20th century.
Clearly, intermarket analysis tools which can identify reoccurring
patterns within individual financial markets and between related
global markets afford traders a broadened trading perspective and
competitive edge in today’s trading environment, which has been
transformed by the mounting globalization and integration of the
world’s financial markets.
The rapidness of change in the global economy and the growing
interdependencies between global futures and equity markets should
make this topic of utmost importance to traders who want their
involvement in the financial markets to be profitable, not just a costly
pastime. Since the markets are a financial version of Darwin’s survival
of the fittest competition, intermarket analysis tools —that build and
expand upon the single-market analysis methods which defined tech-
nical analysis in the late 20th century—demand serious attention.
The Markets Are Constantly Evolving
With the emergence of a new era of global electronic communica-
tions, heralded by the first transatlantic satellite transmission in 1962,
and the subsequent creation of currency, interest rate, oil and stock
index futures in the 1970s and 1980s (following the decision by the
United States to abandon fixed exchange rates in 1971), the world’s
futures and equity markets, previously distinct from one another,
began to coalesce.
The proliferation of financial futures laid the early foundation for
the global integration of the financial markets and for intermarket
analysis to become a necessary component of technical market analy-
sis, as volatility in interest and exchange rates, as well as in oil prices,
created new opportunities and risks for speculators and hedgers,
including multinational corporations.
In the past, trading was conducted on a local level within separate
time zones on individual domestic stock and commodity exchanges.
Now, at the dawn of the 21st century, the melding of the debt, equi-
ty, futures, derivative and options markets throughout the world con-
tinues unabated.
The World’s Futures and Equity Markets Are Linked
Take a look at the chart above (see Figure 1-1). It displays a one-
year (re-scaled) comparison chart of two stock indexes. Notice how
closely they track each other. Try to guess which markets they are.
If you guessed that they are the Nasdaq Composite Index and the
Nasdaq-100 Index, two closely related indexes, you are half right. The
one on the top of the chart is the Nasdaq Composite Index. However,
the one on the bottom is not even a U.S. market. It is a Latin American
Index created by Morgan Stanley Dean Witter to track growth stocks
in Argentina, Brazil, Chile, Columbia, Mexico, Peru and Venezuela.
Trend Forecasting With Technical Analysis 27
Figure 1-1. STOCK INDEXES MIRROR EACH OTHER
Through intermarket linkages, related markets alert traders to impending trend
changes.
Source: www.bigcharts.com
28 Trade Secrets
This chart illustrates the fact that even linkages between seemingly
unrelated markets cannot be ignored by traders as the globalization
of the financial markets continues to evolve.
Already the New York Stock Exchange
®
, the Nasdaq
®
and the Chi-
cago Board of Trade, each mindful of the trend toward market glob-
alization, have begun to build strategic alliances with foreign ex-
changes.
In the year 2000, the New York Stock Exchange announced its
“Global Equity Market
™
” platform, which will involve alliances with
various foreign exchanges, such as the Tokyo Stock Exchange, Paris-
Bourse, Toronto Stock Exchange, Amsterdam Stock Exchange, Stock
Exchange of Hong Kong, Australian Stock Exchange, Brazil’s Bovespa,
Brussels Stock Exchange and Mexico’s Bolsa.
At the same time the Nasdaq, through
alliances with the Australian and Hong
Kong exchanges, the Osaka Securities
Exchange involving the creation of
“Nasdaq Japan
SM
,” the Deutsche Boerse
and the London Stock Exchange in
Europe, and other possible alliances in
Canada and Latin America, is pursuing
its own strategic plan for participation
in the emerging 24-hour global financial
marketplace.
Similarly, the world’s two largest futures exchanges, the Chicago
Board of Trade and Frankfurt’s Eurex exchange, have teamed up to
launch a joint electronic trading platform beginning in the year 2000.
Eventually alliances such as these will allow traders to trade any
financial instrument, anywhere in the world, at any time over seam-
less, electronic global trading platforms.
Having lived through the dismantling of the Berlin Wall, the reuni-
fication of Germany, the breakup of the U.S.S.R. and the end of the
Cold War in the closing years of the last century, it would not surprise
me at all if the New York Stock Exchange and the Nasdaq, for
instance, were to announce the joint creation of a totally compre-
hensive electronic global trading network, in partnership with major
stock and commodity exchanges throughout the world. Necessity is,
after all, the mother of invention.
Linkages between
seemingly unrelated
markets cannot be
ignored by traders
as the globalization
of the financial
markets continues
to evolve.
Before long, trading in the financial markets will be conducted day
and night electronically, in the virtual world of cyberspace far from
the brick and mortar trading floors of today’s stock and futures
exchanges. I can easily envision today’s concepts of “after hours trad-
ing,” “extended trading” and even “open outcry” becoming historical
footnotes to our lexicon, just as the “buggy whip” and the “horseless
carriage” were relegated at the dawn of the 20th century.
With the implementation of twenty-four-hours-a-day trading involv-
ing literally thousands of financial instruments, including esoteric
ones not yet conceived, even small institutional trading organizations
will need to staff their trading operations around the clock. Many
individual traders, however, will suffer from market-induced insom-
nia, as they feel compelled to check on their market positions at all
hours of the night, fearing some external cataclysmic event that trig-
gers an abrupt change in trend direction, or worse yet an overnight
worldwide meltdown of the financial markets.
High-flying Internet, technology and biotechnology stocks are
already traded like commodities by electronic day traders. This stands
to reason, since an uptrend is an uptrend, a trend reversal is a trend
reversal and patterns repeat themselves, regardless of the label that is
put on each market. It doesn’t matter if it’s pork bellies, orange juice,
sugar, Treasury notes, the S&P 500
®
Index, the Swiss franc, crude oil,
Intel or Amgen.
As stock index futures proliferate, index trading expands, Internet
chat rooms continue to bustle with traders sharing trading tips, elec-
tronic day trading becomes recognized as a legitimate “occupation,”
mutual funds trade intra-day, and futures contracts on individual
stocks make their debut, this worldwide intermingling of equities and
futures will accelerate.
Emerging Forces Usher in the New Global Economy
Below is a brief account of some of the more significant techno-
logical, economic, financial and political forces that are converging to
bring about the globalization of the world’s financial markets in the
21st century:
• Advancements in information technologies including microcompu-
ters, satellite, software and telecommunications, which are being
focused on the global expansion and commercialization of the
Trend Forecasting With Technical Analysis 29
30 Trade Secrets
Internet and the development of electronic global communications
and trading networks. Transactions involving the purchase and
sale of financial instruments, tangible property and the raising of
capital will be conducted freely, instantaneously and competitive-
ly on a worldwide level. These developments will render obsolete
the concepts of local financial markets and economic nationalism.
• The expansion of global derivatives trading involving interest rate
futures, stock indexes and options, and the marriage of derivatives
trading with information technologies will continue to meld previ-
ously disparate markets, further increasing market interdependen-
cies and bringing about the total internationalization of the finan-
cial markets.
• Increased global free trade and competition, and the globalization
of multinational corporate financing strategies involving capital
formation, hedging of foreign exchange and interest rate risk,
cross-border listing of shares on multiple exchanges in different
countries, corporate consolidations and cooperative competition
through global alliances, and mergers and acquisitions (particular-
ly within brokerage, investment banking and telecommunications,
as well as between exchanges) across national boundaries.
• Government deregulation involving the banking, brokerage, ener-
gy, telecommunications and transportation industries. Reductions in
marginal tax rates which stimulate economic activity and global
competition, reallocation of capital geographically and from the
public to the private sector, increased productivity, lowered costs,
and spurred innovation in the development of new technologies.
• Productivity gains brought about by advancements in information
technologies positively affecting the cost structure of corporate
enterprises, streamlining and shortening supply chains and cus-
tomer channels.
• Demographic increases in demand for financial assets and broader
participation in privatized, tax-deferred profit sharing and retire-
ment plans by baby boomers.
• The emergence of democratically elected governments, increased
personal rights, free enterprise, private ownership, the privatization
of formerly state-owned enterprises, the encouragement of the spir-
it of entrepreneurship, and the adoption of market-based econom-
ics in developing countries throughout the world, as well as the
expansion of free trade with China and its likely inclusion in the
World Trade Organization.
Market Volatility and Financial Crises
Are Here to Stay
All of these factors, as well as others, have ushered in a new era in
which there will eventually be just one globally integrated network
of financial markets into which all futures, equity and derivative mar-
kets fit as interdependent parts —like pieces in a giant jigsaw puzzle.
If you pick up a financial magazine or
newspaper, or listen to financial news
programs, you’ll hear commentators,
money managers, corporate executives,
financial analysts and economists talk
about a shift in the economic paradigm
referred to as the “new economy” or
“global economy.” This is an emerging
economic world order driven by global
voice, data and video telecommunica-
tions, wireless m-commerce, worldwide
e-commerce and an emerging electron-
ic global financial network encompass-
ing previously independent financial
markets.
Already, when news of an unexpect-
ed change in a government-reported
economic statistic is released, terrorism
occurs in the Mideast, the U.S. Federal Reserve Board or European
Central Bank announces a change in interest rates, or an Asian coun-
try devalues its currency, this news is beamed around the world
instantly by satellite on CNN
™
, CNBC and over the Internet.
Within seconds billions of dollars in financial assets can be con-
verted and redeployed anywhere around the world electronically at
the touch of a mouse button by a large institutional trader without
regard to national, political, social or economic consequences, geo-
graphical considerations, or time of day. A well-placed rumor or fic-
titious press release, perhaps instigated by a new breed of global
Trend Forecasting With Technical Analysis 31
This is an emerg-
ing economic world
order driven by
global voice, data
and video telecom-
munications, wire-
less m-commerce,
worldwide e-com-
merce and an
emerging electronic
global financial
network encom-
passing previously
independent fi-
nancial markets.
32 Trade Secrets
cyber-saboteur, can now set off an explosion of events globally with
instantaneous and potentially harmful financial ramifications, even if
the false information is subsequently proven to be unfounded.
The first instance of the financial market equivalent of an earth-
quake of global proportions occurred on October 19, 1987, as the
world’s futures and equity markets cascaded downward like domi-
noes falling against each other. Once the first domino falls, it precip-
itates a chain reaction that reverberates throughout the world (see
Figure 1-2).
Fortunately, catastrophic damage to the world’s financial markets
and economies was averted in 1987, and during aftershocks from less
powerful earthquakes on the financial Richter scale in the late 1990s.
Yet these events set the stage for what will undoubtedly dot the world
financial landscape in the 21st century, even under the most opti-
mistic global economic scenarios.
As advancements in telecommunications and information tech-
nologies accelerate, time-sensitive global market information be-
comes more widely available over the Internet, and electronic day
trading of stocks, futures, and even mutual funds becomes wide-
spread, uncharted levels of intra-day and inter-day market volatility
may become commonplace in the first decades of the 21st century.
Suffice it to say that “normal” market sell-offs and corrections, some
Figure 1-2. GLOBAL MARKETS REACT TO THE DOMINO EFFECT
Financial crises can spin out of control quickly, as interdependent financial markets
fall, setting off a chain reaction that reverberates worldwide.
Source: Market Technologies Corporation
abrupt and short lived, others protracted, but all very painful and
costly to the unwary, have not been swept under the rug by the new
economic paradigm.
To date, crisis control by the various sectors of the world’s financial
markets including stock and futures exchanges, central banks, clear-
ing organizations, finance ministries, regulatory organizations and in-
ternational banking institutions still apparently operates on an ad hoc
basis. Presently, it is unclear whether or not the existence of a highly
interdependent global communications and trading network, toward
which the world’s financial markets are heading, will mitigate or exac-
erbate global financial crises in the future.
In this climate, the difference between
the financial “haves” and the “have nots”
will be determined by which traders
have access to the most robust inter-
market analysis tools and information
necessary to act decisively, particularly
at the onset of instability in the financial
markets.
This is especially critical for the mil-
lions of baby boomers in the United
States, Europe, Japan and elsewhere,
desperately in need of building and
protecting their wealth to carry them
through their retirement years (poten-
tially lengthened by extended life
expectancies due to breakthroughs in
biotechnology).
With after-tax rates of return on bank deposits and money market
funds barely keeping pace with inflation, and anemic returns on hard
assets such as gold, the only place these baby boomers can turn to
for growth potential and liquidity is the global futures and equity
markets.
These realizations are what prompted me in the mid-1980s to
focus my attention on the broader framework of intermarket analy-
sis, and to develop VantagePoint as an intermarket-based market
forecasting tool. VantagePoint forecasts short-term trends and prices
based upon the pattern recognition capabilities of neural networks.
Trend Forecasting With Technical Analysis 33
Presently, it is
unclear whether or
not the existence of
a highly interdepen-
dent global commu-
nications and
trading network,
toward which the
world’s financial
markets are head-
ing, will mitigate or
exacerbate global
financial crises in
the future.
34 Trade Secrets
It answers these four important questions every trader must grapple
with each day:
• Which direction is the market heading?
• How strong will the move be?
• When will the current trend lose strength, make a top or bottom
and reverse direction?
• What will tomorrow’s trading range be?
In Chapter 5, I will show you how VantagePoint tackles these is-
sues. First, I want to discuss single-market technical analysis and then
compare it with intermarket analysis so you can gain a better under-
standing of how intermarket analysis can dramatically improve your
trading performance.
SINGLE-MARKET
ANALYSIS
Trading With Tunnel Vision
Can Put You on the
Losing Side of a Trade
A
nalysis of the behavior of financial markets for the purpose of
identifying and forecasting market direction has historically
and traditionally been divided into two distinct schools: fun-
damental analysis and technical analysis.
The rationale of fundamental analysis is to make trading decisions
by forecasting market direction based upon underlying economic fac-
tors affecting a particular stock or futures market. For example, a trad-
er sells futures contracts on U.S. Treasury notes anticipating a price
decline due to expected increases in interest rates by the U.S. Federal
Reserve Board; buys corn or soybean contracts based on estimates of
crop damage due to expected drought conditions; or buys shares of
Intel or Oracle on expectations that they will beat the Street’s quar-
terly earnings estimates.
The premise behind technical analysis is that all of the internal and
external factors that affect a market at any given point in time are
already factored into that market’s price. In other words, a market’s
current price is thought to reflect the rational collective judgment of
all market participants, each with his own information pertaining to
that market and perception of what he anticipates the market direc-
tion is likely to be in the near future.
Trend Forecasting With Technical Analysis 35
Chapter 2
36 Trade Secrets
While Numbers Don’t Lie, They Can Be Deceiving
With the assumption that the current price fully discounts all of the
available information about a market and the influences or forces
affecting it, technical analysis, in contrast with fundamental analysis,
does not delve into any of the underlying economic factors that influ-
ence the market.
Instead, technical analysis uses various technical studies, indicators
and market-forecasting theories to analyze market behavior. Historical
market data such as price, volume and open interest of commodity
contracts is examined to identify repetitive patterns, which, if found,
can be used to determine the current market trend, anticipate future
market direction, and provide price targets for entry and exit loca-
tions. This analytic process is depicted in Figure 2-1.
The Goal Is to Forecast Market Trend Direction
While fundamental analysis and technical analysis each have their
own underlying philosophical foundation and specific analytic meth-
odologies that look at the markets from two distinct standpoints, both
methods have the same goal: to identify and forecast the market trend
direction of various financial markets. These include:
• Individual equities, such as Cisco Systems, Intel and Amgen.
• Stock indexes, such as the Nasdaq-100 Index, S&P 500 Index and
Nikkei
®
.
Figure 2-1. TECHNICAL ANALYSIS IS AN ANALYTIC PROCESS
Traders analyze past market data to find repetitive patterns which are used to deter-
mine the market trend and forecast where it’s going next.
Source: Market Technologies Corporation
Technical
Studies,
Indicators
and Theories
Market
Data
Repetitive
Price
Patterns
Goal
Identify Current Trend
Forecast Future Trend
and Prices
Estimate Price Targets
• Interest rates, such as 10-year U.S. Treasury notes, 5-year U.S.
Treasury notes and eurodollar.
• Currencies, such as the U.S. Dollar Index, Swiss franc and British
pound.
• Energies, such as crude oil, heating oil and gasoline.
• Metals, such as gold, silver and platinum.
Through either fundamental or technical analysis, traders attempt
to form expectations about the trend direction of each market, and
make trading decisions with the hope of realizing a profit if their mar-
ket forecasts prove to be correct.
The underlying assumption made by fundamentalists and techni-
cians is that their methods result in superior trading performance.
This has been a controversial subject over the years, with counter-
vailing arguments that the practices of both fundamental and techni-
cal analysis are futile efforts.
From my experience over several decades as a trader and techni-
cal analyst, I am convinced that being able to make a reasonably
accurate short-term trend forecast of market direction improves the
outcome of the decision-making process —resulting in more prof-
itable trading. However, even if a trader were able to make a perfectly
accurate forecast of market direction, he would still have one final
challenge to surmount. This involves market timing.
You Can Play the Markets, or
You Can Time the Markets
Once a trader analyzes a specific market and forms an opinion
about the likely trend direction of that market, he must still decide
when to get into or out of a position and at what price.
In all walks of life, timing is everything. In the financial markets, if
you forecast the trend direction correctly but your timing is off (by
just one day or even an hour or less) you can still end up losing
money.
Historically, market timing has been particularly challenging for
traders in the futures markets, due to their price volatility, low margin
requirements and high degree of leverage. As the new breed of elec-
tronic day traders moves into and out of high-flying tech stocks with
Trend Forecasting With Technical Analysis 37
38 Trade Secrets
the same speed and indifference that futures traders buy and sell con-
tracts on the Japanese yen or crude oil, more equity traders now con-
cern themselves with market timing than ever before.
As a trader there is nothing more frustrating than to anticipate the
trend direction correctly, get into a position slightly too soon, have
the market go against you, get stopped out, and then have the mar-
ket turn around and move in the direction that you expected. When
this happens, you end up either sitting on the sidelines after taking a
loss, or trying to chase after the market. Identifying the current trend
direction, while important, is not enough. You must also be able to
anticipate when the market is poised to make a top or bottom and
change direction.
Once you can forecast the trend direction, can identify turning
points, and have an expectation of the next day’s price range to help
you determine entry and exit locations, there’s really nothing more in
the way of analysis necessary. Now it’s just a matter of “pulling the
trigger.”
Technical Analysis Has Not Kept Pace
With the Markets
If you read any recent issues of popular financial magazines you’ll
find numerous articles on technical analysis with current price charts
and hypothetical track records, nearly identical in content to articles
published in the financial press ten, twenty, and even thirty years ago!
These updated articles are undoubtedly enlightening to novice trad-
ers just beginning to learn about technical analysis and the financial
markets. Remember how excited you were when you first learned
how to spell “Exponential,” “Fibonacci,” and “Stochastic” and under-
stood what they meant? I cannot begin to count how many dozens
of articles and books on technical analysis I have read over the past
several decades rehashing, for instance, the differences between var-
ious types of moving averages and comparing their effectiveness at
reducing the “lag effect.”
This subject was covered in detail in Perry Kaufman’s Commodity
Trading Systems and Methods originally published in 1978, and in
Charles Patel’s Technical Trading Systems for Commodities and Stocks
published in 1980—to name just two classics in my personal library.
The list could go on and on.
There is a typical path that new traders seem to follow. First, they
learn the ABCs of technical analysis by reading a few introductory
books or magazine articles, or watching educational videos or CDs.
These traders learn about price formations and chart patterns such as
head-and-shoulders, flags, islands, pennants, triangles, support and
resistance trend lines, gap patterns and price channels. Then the
traders might attend free trading seminars in their hometowns spon-
sored by an e-brokerage firm or software vendor and learn about
other technical indicators like candlesticks or moving averages.
Eventually new traders buy mass-mar-
keted trading software programs that
automate the calculations of various sin-
gle-market indicators. After developing
and testing different trading strategies
built around some of these concepts,
such as moving average crossover ap-
proaches, many traders begin thinking
that they are on the verge of getting rich,
and will soon be able to quit their day
jobs and become full-time electronic
day traders. This cruel fallacy has been
perpetuated by alluring promotional ad-
vertisements in the financial industry for
as long as I can remember.
Many of today’s traders have little, if any, personal knowledge of
prior stock market routs, including the 1987 crash, not to mention the
torturous decline of 1974. Just ask any veteran traders like myself
about their trading experiences during the stock market debacle of
1974, when the Dow Jones Industrial Average dropped nearly 50%
from its previous high, and you’ll get an earful. That’s when I learned
the painful lesson about the psychological struggle between greed
and fear, with the latter ultimately demonstrating its more powerful
grip on the human psyche.
Protracted bull markets encourage novices to overestimate their
skills as technicians and traders. Greed seduces traders into forming
unrealistic expectations of annual market returns and the risks inher-
ent in trading. Under such conditions traders develop a false sense of
Trend Forecasting With Technical Analysis 39
Identifying the
current trend
direction, while
important, is not
enough. You must
also be able to
anticipate when
the market is
poised to make a
top or bottom and
change direction.
40 Trade Secrets
self-confidence. They begin to expect quick results, like finding the
Holy Grail trading system and achieving overnight riches without
having to work for it. If it were that easy, every trader would be a self-
made millionaire.
Too often new traders assume that heavily promoted or inexpen-
sive trading tools must be the ones to use, since after all so many
other traders are already using them. Unfortunately, technical analy-
sis tools are not like VCRs, where the most popular ones are usually
the best.
If the masses of traders look at the markets from the same narrow
single-market perspective and lose money doing so, then if you like-
wise limit the scope of your analysis,
common sense would tell you that you
should also expect to lose your money.
This doesn’t take a Ph.D. degree in
applied mathematics to figure out. It’s
just high-school math: if A=B and B=C,
then A=C. Yet too many newcomers to
the markets start off on this losing path
and stay on it until their trading capital
is depleted.
It is foolish to think that at first you
can get by using inexpensive single-
market analysis tools to build up your
trading account until you can afford to
get the right tools. If your spouse devel-
ops a life-threatening heart condition,
you wouldn’t pick a cardiologist based
on how cheap his fees are, with the in-
tention that if the condition improves a little you’ll switch to a more
capable doctor.
Traders are bombarded with a barrage of market information from
a myriad of sources including financial television channels, high-traf-
fic financial websites and Internet chat rooms. While this explosion
of information allows traders unprecedented access to the research
and opinions of many reputable technical analysts, advisors and
money managers, it also exposes traders to the increasingly slick and
deceptive use of misinformation and “disinformation” by charlatans
posing as market gurus in cyberspace.
To succeed in the
financial markets,
you cannot treat
your trading lightly,
as if it’s a hobby.
You must treat it
like a business
and that means you
will need to spend
time and money to
succeed. Do your
homework and
get the best analy-
sis tools from the
get-go.
The pervasiveness of, and ease of access to, all this information
makes today’s generation of traders prone to herd behavior. This herd
mentality results in a psychological phenomenon referred to as
“thought contagion,” which contributes to industry loss statistics.
In the case of futures traders, for instance, it is reported that
upwards of 95% lose their money. If the commercial airline industry
had a comparable fatality record, no one in their right mind would
fly, and Amtrak
®
would be hailed as the safest, most convenient way
to travel cross-country.
To succeed in the financial markets, you cannot treat your trading
lightly, as if it’s a hobby. You must treat it like a business and that
means you will need to spend time and money to succeed. Do your
homework and get the best analysis tools from the get-go, or don’t
bother trading and take a trip to Las Vegas instead. You’ll have a lot
more fun and a lot less aggravation.
Traders Need to Take Off Their Blinders
While even novice traders readily admit that the world’s financial
markets are interconnected, and acknowledge intermarket dynamics
as important factors in determining the trend direction of individual
markets, an overwhelming percentage of traders, particularly those
new to the futures and equity markets in the last few years and espe-
cially those with limited capital, are still either unfamiliar with inter-
market analysis or just don’t know how to incorporate it into their
trading.
These traders hear and read every day about how the markets are
interconnected and affect each other —but don’t really know how to
make the connection themselves. So, like ostriches with their heads
in the sand, they stick with single-market analysis methods and lag-
ging indicators, until it’s too late.
They continue to wear restrictive technical analysis blinders, con-
tent to focus their attention on only one market at a time, as though
each market trades in total isolation. This results in an incomplete
perception of what is really happening—and more importantly what
is about to happen—in the markets that they are trading.
No wonder so many traders run for cover like scared rabbits when
the markets get choppy or there is a sudden trend reversal. If this is
Trend Forecasting With Technical Analysis 41
42 Trade Secrets
how you are currently performing your analysis, you are making your
trading decisions in an intermarket “vacuum.” This can only lead to
failure. If you have a relatively small account to work with, your sit-
uation is even more precarious because you have little margin of
error before your capital is exhausted.
The Blind Men and the Elephant
The “Six Blind Men and the Elephant” parable reminds me of the
limitations of single-market analysis. Each of the men touched one
part of an object that they had discovered in hopes of determining
what it was. Here’s how they each described what they had found:
The first blind man insisted it was some
type of spear. It was sharp, hard, coarse,
and sturdy.
The second blind man concluded it was
some type of rope or whip.
The third blind man thought it was some
type of a wall, since it had a rough tex-
ture and was very firm.
The fourth blind man decided that they
had found some type of an animal, proba-
bly a large snake, since it was long, easy
to bend and had a strange texture.
The fifth blind man thought that they
had found some type of plant. It felt like a
large leaf because of its texture and size.
The sixth blind man was convinced
that they had found a log or branch of
a tree, since he had already heard from
one of the other men that the object felt
like a leaf.
They were all wrong. They had
each only touched a small part of
an elephant and formed incorrect
conclusions based on their limited
observations. The financial mar-
kets are no different. If this had
been a trade, it would have been
a losing one! While an analysis of
each individual market is still
important, it is no longer sufficient
because it fails to take into con-
sideration the whole picture.
As the global integration of the financial markets continues to
extend throughout the financial industry, traders who limit their
analysis to a single market’s past prices (or rely exclusively upon sub-
jective chart pattern analysis or linear forecasting methods such as
trend lines) for clues regarding a market’s future trend direction, will
be at a severe competitive disadvantage. These traders will undoubt-
edly end up watching their trading accounts dwindle, while informed
traders who incorporate intermarket analysis into their trading strate-
gies will be in a position to amass substantial wealth.
In the next chapter, I will discuss intermarket analysis in more
detail, and show how your trading can profit from it.
Trend Forecasting With Technical Analysis 43
INTERMARKET ANALYSIS
Seizing Trading Opportunities
in a Shrinking World
O
ver the past few decades, when the financial markets were
less volatile and tended to trade independently of one
another, single-market methods of analysis were the main-
stay of technical analysis and rightfully so. However, at this juncture,
a narrow characterization of the markets, with its focus (if not preoc-
cupation) on the inward analysis of each individual market, is much
too limited. Traders need to expand their perspective to take into
consideration external factors that affect each market.
Here’s a simple analogy. Imagine yourself as a licensed pilot pre-
paring to fly your private plane from New York City to Washington,
D.C., just before dusk one summer evening. Everything on your pre-
flight checklist indicates that all of the plane’s internal operating sys-
tems are functioning properly, including visual fuel and oil checks,
control movements, altimeter, compasses, flaps, mags and engine
runup. However, you neglect to inquire about one critical external
factor: the flight service in-route weather briefing.
In effect, by ignoring the external environmental context in which
your plane will be flying, you are implicitly assuming that either the
weather conditions will be favorable, or will not adversely affect your
flight. This could make for a “hard landing” (no pun intended) if in
fact the weather conditions prove unfavorable for such a flight.
Is trading Treasury notes, crude oil, the Nasdaq-100 Index or the
Japanese yen any different if you are ignoring the broader intermar-
ket forces affecting these individual markets?
Trend Forecasting With Technical Analysis 45
Chapter 3
46 Trade Secrets
The cliché “what you don’t know can’t hurt you” is false. Ignorance
is not bliss when it comes to piloting planes or trading futures or equi-
ties. If you have the right tools, which give you pertinent information,
you will be able to make calculated decisions; if you don’t, you are
just gambling, either with your life or with your hard-earned money.
Sure, it is worthwhile to analyze the behavior of each individual
market. I still do a lot of that in my trading. Failed double tops, bro-
ken trend lines and prices cutting above or below their 50-day or 200-
day moving average are still useful indicators of market direction, if
for no other reason than the fact that they are followed by so many
traders and acted upon through mass psychology. However, it is not
good enough to look only at each individual market by itself.
Popular single-market technical analysis indicators such as moving
averages and chart pattern formations are lagging indicators which
look retrospectively at an individual market’s past data in an effort to
identify reoccurring patterns which can then be extrapolated into the
future. This type of analysis really boils down to looking at where the
market has been, and trying to guess where it is going.
Since the objective of technical analysis is trend identification and
forecasting, it would stand to reason that this goal could best be
achieved by working with leading indicators that anticipate changes
in trend direction.
I prefer to forecast market direction prospectively in a manner that
captures the character and nature of today’s interdependent financial
markets. This can be accomplished by using intermarket analysis tools
comprised of leading indicators that forewarn whether an existing
trend is likely to continue or is about to change direction. This takes
the guesswork out of trading.
Intermarket Analysis in the Equity
and Commodity Markets
Intermarket analysis had its genesis in both the equity and com-
modity markets. Traditional technical analysis within the equity mar-
kets has historically looked at relationships among individual stocks,
sectors and broad market indexes.
Additionally, comparisons between the debt and equity markets
have been made, as the effects of fluctuating interest rates, inflation-
FIGURE 3-1. DEBT AND EQUITY MARKETS AFFECT EACH OTHER
Comparison chart examines the price relationship between 10-year Treasury notes
and the S&P 500 Index.
Source: VantagePoint Intermarket Analysis Software
ary expectations, and central bank policies have played an increas-
ingly important role in determining the market direction of equities.
More recently, comparisons between broad market indexes repre-
senting various stock markets around the world have been made.
Intermarket analysis within the equity markets include the follow-
ing comparisons:
• Domestic broad market indexes to one another.
• Market sectors to the broad market indexes.
• Individual stocks to broad market indexes.
• Individual stocks to one another within a sector.
• The relationship of price, time and volume to one another.
• The advance/decline line compared to the performance of broad
market indexes.
• Movements in interest rates to movements in stock indexes such as
the relationship between 10-year Treasury notes and the S&P 500
Index, as shown in Figure 3-1.
Trend Forecasting With Technical Analysis 47
10-year Treasury notes
S&P 500 Index
48 Trade Secrets
Figure 3-2. STOCK INDEXES IN DIFFERENT COUNTRIES AFFECT EACH OTHER
Comparison chart examines the price relationship between the Nikkei in Japan and
the Dow Jones Industrial Average in the U.S.
Source: VantagePoint Intermarket Analysis Software
• Stock indexes, such as the Nikkei 225 and FTSE 100, are compared
to similar market indexes in other countries such as U.S. stock
indexes including The Dow
SM
or Nasdaq.
Figure 3-2 depicts a comparison chart of the Nikkei and the Dow
Jones Industrial Average, showing how these two global markets
behave relative to one another.
By their nature, the commodity markets have historically lent them-
selves to intermarket analysis. With both a cash market and numer-
ous futures contract months existing simultaneously on a given com-
modity, and with such closely related commodity complexes as the
grains, meats, currencies, interest rates, stock indexes, metals and
energies, intra-commodity and inter-commodity spread analysis has
been an integral part of technical analysis of the commodity markets
for decades.
Spreads between futures markets of related instruments are looked
at to gain additional insight into market direction. These include:
• The “NOB” (Notes Over Bonds) spread between 10-year Treasury
notes and 30-year Treasury bonds.
Dow Jones
Industrial Average
Nikkei
Trend Forecasting With Technical Analysis 49
• The “TED” (Tbills-Eurodollar) spread between 90-day Treasury bills
and the 90-day eurodollar.
• Spreads between bonds and the Bridge/CRB
®
Futures Price Index,
the U.S. Dollar Index, gold and crude oil, to name a few.
Intermarket comparisons between futures and the equity markets
highlight short-term confirmation or divergence, which provides in-
sight into impending changes in market trend direction. Futures can
be monitored as an early barometer of the equity markets. Futures on
the S&P 500 Index, Treasury bonds and notes, as well as other finan-
cial futures markets including crude oil, the Bridge/CRB Futures Price
Index and the U.S. Dollar Index are increasingly looked upon as hav-
ing strong influences on the equity markets.
For instance, higher Bridge/CRB Futures Price Index prices, sug-
gesting higher inflation down the road for various commodities, tend
to drive Treasury notes prices lower (and interest rates higher) which
is also negative for those sectors of the equity markets linked to these
commodities including the agricultural, banking, energy, metals and
industrials sectors.
Globally related markets can be analyzed with regard to their con-
firmation or divergence from one another over time, in response to
various global and domestic economic considerations. For instance,
changes in interest rates (effected by the U.S. Federal Reserve Board,
European Central Bank or the Bank of Japan), currency devaluations
or sudden spikes in crude oil prices have a pronounced effect on fu-
tures and equity markets worldwide.
Intermarket analysis between like debt instruments in different
countries also offers worthwhile cues concerning future global trends
in interest rates. For example, spreads involving government notes
and bonds from various countries can be examined with respect to
each other, as global arbitrage of interest rates tends to keep interna-
tional debt markets synchronized.
No Market Is Exempt From Globalization
Every market, both domestically and internationally, now appears
to have some effect on every other market, however seemingly dis-
tant and unrelated. A thorough analysis of the outlook of any one
market is now incomplete without looking at it within an intermarket
context.
50 Trade Secrets
Figure 3-3 shows nine related markets that are examined by
VantagePoint’s 10-year Treasury notes program. As the software con-
tinues to be refined as part of my firm’s ongoing research effort to
increase VantagePoint’s predictive accuracy, related markets will
change and more will be added.
Why Markets Converge or Diverge
Although there are direct and inverse relationships that on the sur-
face appear to link markets to one another when they are examined
two at a time, these linkages are neither fixed nor linear in nature.
Instead they are dynamic, and have varying strengths, as well as vary-
ing leads and lags to one another that shift over time.
With the increased emphasis today on on-line day trading (where
twenty minutes is considered long term) novice traders expect the
effects on a market from related markets to be instantaneous. Traders
think that all they have to do is look at what Treasury bonds or notes
are doing at any moment in time to get cues on what the stock mar-
ket will do next. However, this is not how the financial markets work.
Sometimes the order of cause and effect is reversed, with stocks
seeming to lead bonds and notes while at other times the Treasurys
appear to lead stocks. Like the chicken and egg dilemma, it is very
hard to discern which comes first.
Figure 3-3. FINANCIAL MARKETS ARE ALL CONNECTED
Nine related markets are examined by VantagePoint’s 10-year Treasury notes pro-
gram to find hidden patterns and relationships.
Source: Market Technologies Corporation
Eurodollar
U.S. Dollar Index
S&P 500 Index
T-Bonds Swiss Franc
NY Light Crude Oil
Comex Gold
Bridge/CRB Index 5-Year T-Notes
10-Year Treasury Notes
Trend Forecasting With Technical Analysis 51
Intermarket Dynamics Must Be Taken
Into Consideration
Traders are still too preoccupied with the inward analysis of each
market, ignoring the interdependencies of the financial markets and
their effects on one another, which have become more pronounced
as the markets have become increasingly globalized.
Additionally, scant progress has been made at objectively (quanti-
tatively) rather than subjectively (qualitatively) identifying repetitive
patterns in market data, necessary to perform effective forecasting.
Now it is imperative for traders to adopt an intermarket perspective
and incorporate intermarket analysis into their trading strategies, in
order to deal with the global financial markets as they really exist.
If you look at the planet Saturn through an inexpensive, low-pow-
ered telescope, you won’t see the rings that surround it. They are
there, but the tool you are using doesn’t have the capability to dis-
cern them. The same is true for how you look at the markets. While
the interconnections are there, you may not see them—but other
traders do.
Failing to factor into their trading strategies the linkages between
related markets, many traders remain oblivious to the underlying
intermarket forces or market synergy that increasingly affects price
movements in today’s global markets. Unquestionably, this narrow
analytic perspective contributes to the financial fatality rate, among
both experienced and novice traders.
I think it is absurd when I hear traders say that having an accurate
short-term forecast of market direction would be of no benefit to
them in their trading. These traders obviously do not understand the
basic purpose of technical analysis. They have become so caught up
with back-testing number crunching on each individual market that
they have lost sight of the forest for the trees.
Early Attempts at Intermarket Analysis Fall Short
Due to the complexity of the dynamic interactions between finan-
cial markets, it is difficult for the average trader to perform even rudi-
mentary intermarket analysis. Nevertheless, technical analysts have
devised various ways to do so. Here are some popular, yet in my
52 Trade Secrets
opinion somewhat ineffective, ways that analysts and traders attempt
to quantify the effects of related markets:
• Price charts on two markets are compared to one another, and the
difference between the two markets’ prices on a minute-by-minute,
hourly, daily, weekly, or monthly basis is calculated and presented
graphically or numerically, as an indication of future market direc-
tion.
• A ratio of the prices representing two markets is calculated and pre-
sented graphically or numerically to show how the two markets
have behaved relative to one another in the past, to help anticipate
what they are likely to do in the future.
• A statistical linear correlation analysis on two markets is performed.
This approach measures the degree to which the prices of one
market move in relation to the prices of the second market. The
mathematical indicator used to measure correlation is known as a
statistical correlation coefficient.
Tracking Related Markets Pays Off
As the number of markets to be explored from an intermarket per-
spective increases, the effectiveness of using any of the previously
mentioned methods rapidly diminishes. These methods of analyzing
intermarket relationships are limited to price comparisons of only two
markets at a time, often assuming incorrectly that the effects of one
market on another occur without any leads or lags. In addition, such
methods presuppose the effects are linear in nature in a sort of one-
to-one causal relationship. This, too, is not realistic with respect to
how the global financial markets function.
Leads and lags exist between domestic and international econom-
ic activity and the financial markets, and between related domestic
and global financial markets. Sometimes the effects may not be dis-
cernible for days, weeks or months, as in the case of inflationary pres-
sures or the implementation of central bank monetary policies that
take time to work their way through the global economy.
To examine the multiple effects of as few as five or ten related mar-
kets simultaneously on a target market, methods such as linear cor-
relation analysis and subjective chart pattern analysis quickly reveal
their inadequacy as forecasting tools.
For most traders it is just too difficult and time consuming to keep
up with more than two or three related markets simultaneously and
to figure out how they influence each other. Two or three charts can
be “eyeballed” at the same time, or a linear correlation can be calcu-
lated between two markets at a time. However, these approaches fail
to capture the simultaneous combined effects of numerous related
markets on a specific target market.
Full Field of Vision Is Critical
You can get a sense of the difference between single-market analy-
sis and intermarket analysis if you put a hand over one of your eyes
and try walking around the room. With only one eye open, your field
of vision is limited and your ability to visualize your surroundings is
severely restricted. This is how most traders make their trading deci-
sions, with a narrow focus on each market in isolation. Next drop
your hand and walk around the room with both eyes open. Now you
are really benefiting from your full field of vision. Don’t you think you
would have an advantage if you tackle your trading the same way—
with both eyes wide open?
Here’s a different way to visualize the added depth that intermarket
analysis brings to bear on your trading decisions. Consider the case
of the Captain of the ocean liner Savvy Trader, navigating the treach-
erous waters of the north Atlantic early last century. Trying to pick the
safest route to his destination, he scanned the horizon for hazards; he
took notice of wind speed, air temperature, wave frequency and
height.
At a distance, he spotted a large floating chunk of ice. Carefully plot-
ting its speed and direction over time, he extrapolated its movement
and concluded that the ice wasn’t a threat to his ship. That night, how-
ever, the Captain was awakened by a loud crash. The iceberg had
slammed into his ship. The Captain was confused, shocked and angry.
He had not anticipated that this would happen. While meticulous-
ly examining the conditions on the surface, he was unaware of critical
conditions beneath the surface. The bulk of the massive iceberg had
been hidden from view; warming water temperatures had melted the
ice, increasing its speed. Changes in underwater currents had affected
its direction much more than surface winds. At the time (before sonar,
infrared and satellite imaging were available), the Captain did not have
tools capable of predicting the direction of the iceberg.
Trend Forecasting With Technical Analysis 53
54 Trade Secrets
A similar situation confronts today’s traders who limit themselves to
single-market analysis and lagging indicators to determine market
direction. What they are doing is not wrong; it’s simply insufficient.
Intermarket analysis tools give today’s traders the same edge in their
decisions that sonar gives today’s ship captains.
You do not need to throw the baby out with the bath water, though.
I am not suggesting that you should stop performing single-market
technical analysis or abandon the use of trend following methods that
have played a central role in technical analysis for decades.
Many popular single-market technical indicators are useful to one
degree or another to analyze internal market behavior. However, they
are most effective when used in combination with intermarket analy-
sis to get a three-dimensional view of each market. This is not a case
of “either-or.” Intermarket analysis should be used as a confirmation
filter to single-market indicators. In this manner, marginal trades can
be filtered out and avoided.
This distinction can be visualized by contrasting the rectangle on
the left side of Figure 3-4, representing single-market analysis, with
the three-dimensional cube on the right side representing intermar-
ket analysis.
Figure 3-4. INTERMARKET ANALYSIS GIVES MORE DEPTH TO YOUR ANALYSIS
Single-market analysis looks only at each market by itself. Intermarket analysis
adds a third dimension by taking into consideration the effects of related markets.
Source: Market Technologies Corporation
Intermarket analysis builds upon the strengths of single-market
analysis, adding another dimension to the analytic framework so that
the behavior of each market can be analyzed internally as well as
within a broader intermarket context.
In Figure 3-5, I have outlined some of the distinctions, from a prac-
tical trading standpoint, between intermarket analysis and single-mar-
ket analysis.
Trend Forecasting With Technical Analysis 55
Figure 3-5 INTERMARKET ANALYSIS BROADENS THE SCOPE OF SINGLE-MARKET
ANALYSIS AND OVERCOMES MANY OF ITS LIMITATIONS
Differences between intermarket analysis and single-market analysis highlight the
importance of adding intermarket analysis to your trading arsenal.
Source: Market Technologies Corporation
Intermarket Analysis With
Trend Forecasting Indicators
? Looks at multiple markets simul-
taneously. Analyzes their effects
on a target market.
? Leads the market, pinpointing
trading opportunities as they are
about to unfold.
? Traders can enter and exit trades
just as the trend is changing.
? Trends are identified as they are
developing so traders catch a big-
ger portion of each move.
? Stops are placed based on how
related markets are affecting the
market being traded.
? False trading signals are mini-
mized because the full picture is
taken into consideration, not
just a small piece of it.
Single-Market Analysis With
Trend Following Indicators
? Looks at one market at a time.
? Lags the market, causing traders
to miss the start of new trends.
? Trades are often triggered several
days after the trend has changed
direction.
? Often gives back a large portion of
profits, sometimes turning a prof-
itable trade into a losing trade.
? Stop placements are determined
by looking at the market being
traded, often based on commonly
used indicators such as trend
lines, which tend to cluster stops
near one another.
? False signals are common during
sideways markets resulting in
frequent losing trades.
56 Trade Secrets
Intermarket Analysis: In the Right Place
at the Right Time
A formal, quantitative methodology to implement intermarket
analysis, such as I have applied since 1991 within VantagePoint, is
neither a radical departure from traditional technical analysis, nor an
attempt to undermine or replace it. Intermarket analysis, in my opin-
ion, is simply the next logical developmental stage in the evolution
of technical analysis, given the global nature of today’s interdepen-
dent, highly complex economies and integrated financial markets.
If you need to dig a hole in the
ground that is a foot deep and a foot
square, you wouldn’t do it with a tea-
spoon. Similarly, if you want to stir a
cup of coffee, you wouldn’t use a
spade. You’ve got to use the right tool
for the job. Today’s markets are inter-
dependent and interconnected. That
means you need to perform intermar-
ket analysis. Let’s call a spade a spade
—single-market analysis by itself is
simply not adequate, period.
I found the best way to implement
intermarket analysis is through the use
of neural networks. They excel at find-
ing reoccurring patterns and relation-
ships between related markets, as well
as patterns within a single market. Once
found, these patterns are used to make
highly accurate forecasts of market di-
rection.
By analyzing the effects of related markets (particularly the futures
markets which are inherently oriented toward anticipating future
price levels), important early warnings of impending changes in mar-
ket direction can be gleaned from intermarket data well before these
changes begin to show up on the charts of traders who limit the
scope of their analysis to each individual market.
VantagePoint, for example, using extensive intermarket data, fore-
casts the market direction for the next two and four days and fore-
I found the best
way to implement
intermarket analy-
sis is through the
use of neural net-
works. They excel
at finding reoccur-
ring patterns and
relationships
between related
markets, as well as
patterns within a
single market. Once
found, these pat-
terns are used to
make highly accu-
rate forecasts of
market direction.
Trend Forecasting With Technical Analysis 57
warns, through its “Neural Index” indicator, whether a target market
is expected to make a top or bottom within the next two days. This
is all done automatically through the pattern recognition and fore-
casting capabilities of neural networks, which I will discuss in
Chapter 6.
Let’s face it, even my eleven-year-old son can look at a bar chart
and tell you what happened in the stock market yesterday and over
the last few days or weeks. Hindsight is 20/20; but you can only prof-
it by having foresight. You cannot make money tomorrow or next
week based on what happened yesterday or last week. You can only
make money if on a consistent basis you can anticipate, with rea-
sonable accuracy, what is going to happen in the near future.
If you had Tuesday’s Investor’s Business Daily
®
or The Wall Street
Journal
®
available to you every Monday morning with your coffee—
one day in advance—you could quickly become the wealthiest per-
son in the world. Why? Because you would have 100% accurate infor-
mation on the following day’s prices and would know exactly what
to expect next.
The Only Thing Certain Is Uncertainty Itself
Unfortunately, it is no more possible to make 100% accurate fore-
casts of the financial markets than to get The Wall Street Journal one
day in advance. Forecasting inherently involves mathematical proba-
bilities, not certainty. However, a market forecast does not need to be
perfect to tilt the odds in your favor.
To have a substantial competitive advantage over other traders, all
you need is a reliable forecast that can consistently beat a coin toss.
VantagePoint’s nearly 80% predictive accuracy at forecasting short-
term market direction gives you more than enough edge over other
traders.
Widely used technical indicators can be applied to intermarket
analysis in innovative ways. I have been very successful in accom-
plishing this with VantagePoint, in which neural networks make
short-term forecasts of moving averages.
In the next chapter I will discuss moving averages, showing you
how I turned them into a powerful leading indicator within Vantage-
Point through the use of intermarket analysis and neural networks.
TODAY’S MARKETS
HAVE CHANGED
Why Trend Forecasting Beats Trend
Following and How Traders Can Profit
M
oving averages are one of the most popular technical indi-
cators used to identify the trend direction of financial mar-
kets. Moving averages form the basis of a myriad of single-
market trend following trading strategies, ranging from the popular
4-9-18-day moving average “crossover” approach to the widely fol-
lowed 50-day and 200-day simple moving averages used to assess the
market trend direction of broad market indexes and individual stocks.
Figure 4-1, on the next page, depicts the Dow Jones Industrial
Average with its 200-day moving average superimposed on the daily
price chart. This indicator is used extensively by technicians and
traders as an indication of The Dow’s trend direction. When The Dow
closes above its 200-day moving average, the market is considered to
be in an uptrend. When The Dow closes below its 200-day moving
average, the uptrend is considered to be “broken” as a bearish senti-
ment permeates the market.
Moving averages are precisely calculated according to specific
mathematical formulae. This makes moving averages an objective
way to determine the current trend direction of a market, and antici-
pate its most likely future direction. This is in sharp contrast to sub-
jective approaches to trend identification based on visual chart analy-
sis of reoccurring patterns such as head-and-shoulder formations,
flags, triangles and pennants, etc.
Trend Forecasting With Technical Analysis 59
Chapter 4
60 Trade Secrets
Mathematically, moving averages filter out the random “noise” in
market data by smoothing out fluctuations and short-term volatility in
price movement. Graphically superimposing a moving average on a
price chart makes it easy to visualize the underlying trend within the
data.
Moving Averages Are Lagging Indicators
However, traditional moving averages have one very serious defi-
ciency. They are a “lagging” technical indicator. This means that mov-
ing averages, due to their mathematical construction (averaging prices
over a number of prior periods), tend to trail behind the current mar-
ket price. In fast moving markets, where the price is on the verge of
rising or falling precipitously, this lag effect can become very pro-
nounced and costly.
The shorter the length of a moving average, the more sensitive it
will be to short-term price fluctuations. The longer the length of a
moving average, the less sensitive it will be to abrupt price fluctua-
tions. Therefore, short moving averages lag the market less than long
moving averages, but are less effective than long moving averages at
smoothing or filtering out the noise.
Figure 4-1. FOLLOWING THE TREND OF THE DOW JONES INDUSTRIAL AVERAGE
WITH ITS 200-DAY MOVING AVERAGE
The 200-day simple moving average is a popular trend following indicator of The
Dow’s trend direction.
Source: www.bigcharts.com
Dow Jones
Industrial Average
200-day moving
average
Trend Forecasting With Technical Analysis 61
Trades based upon moving averages are often late to get into and
out of the market compared to the point at which the market’s price
actually makes a top or bottom and begins to move in the opposite
direction.
Figure 4-2 depicts a chart of daily prices of the U.S. Dollar Index
compared to its 10-day simple moving average. Because of the steep
price increase prior to the market making a top, the moving average
actually continues to increase in value, even as the market begins to
drop before cutting the moving average from above to below.
Depending on the price movement and the type and size of mov-
ing average used, this “response” delay can be financially devastating
under extreme circumstances, such as waking up one morning and
finding yourself on the wrong side of an abrupt trend reversal involv-
ing a lock-limit futures position.
The lag effect, which to date has been the Achilles’ heel of moving
averages, has presented a challenge to technical analysts and traders
for decades. Extensive research has been directed at finding ways to
reduce the lag, while at the same time retaining the benefits of mov-
ing averages.
Figure 4-2. U.S. DOLLAR INDEX WITH ITS 10-DAY SIMPLE MOVING AVERAGE
Chart of daily prices of the U.S. Dollar Index with its 10-day simple moving average
shows how moving averages lag behind the market.
Source: VantagePoint Intermarket Analysis Software
Market
made a top
here
Price
crosses
moving
average
62 Trade Secrets
To accomplish these two goals, numerous variations of moving
averages have been devised. Each has its own mathematical con-
struction, effectiveness at identifying the underlying trend of a mar-
ket and ability to overcome the lag effect. The three most common
types of moving averages relied upon by technical analysts and
traders for decades are the simple, weighted and exponential moving
averages.
Simple Moving Averages
A simple moving average is the arithmetic “mean” or average of a
price series over a selected time period. As the market moves forward
in time, the oldest price is removed from the moving average calcu-
lation and replaced by the most recent price. This allows the moving
average to “move,” thereby keeping pace with changes in the mar-
ket’s price. A simple moving average lags behind the market because
it gives equal weight to each period’s price. This limitation is what has
prompted the use of weighted and exponential moving averages.
Weighted and Exponential Moving Averages
A weighted moving average attempts to reduce the lag by giving
more weight to recent prices, thereby allowing the moving average
to respond more quickly to current market conditions. The most pop-
ular version is the linearly weighted moving average.
An exponential moving average, like a weighted moving average,
gives more weight to recent prices, while differing from a weighted
average in other respects.
Moving Averages Are Popular —
But Something’s Missing
Virtually every book on technical analysis devotes at least one
chapter to moving averages, describing detailed accounts of the var-
ious means that technicians have devised to reduce the lag effect.
While each type of moving average has its own strengths and
weaknesses at smoothing the data and reducing the lag, none of
them, by virtue of being based solely on past single-market price
data, have been successful at eliminating the lag.
Trend Forecasting With Technical Analysis 63
Using microcomputers and strategy back-testing software, since the
early 1980s traders have optimized the sizes of moving averages in an
effort to best fit them to each specific target market. For instance, the
moving average length selected for Intel might be entirely different
than for Applied Materials, Treasury notes or the Japanese yen.
In fact, the moving average length selected for a specific market at
one point in time or under certain market conditions is often differ-
ent than at other times or under other conditions. These observations
encourage traders to re-optimize moving averages periodically (and
sometimes too frequently), in a futile attempt to keep them respon-
sive to current market conditions.
Moving Average Crossovers Lead to Whipsaws
Moving averages can be used as
building blocks in more complex tech-
nical indicators, in which, for instance,
two moving averages are compared to
one another. This is done either by sub-
tracting the value of one moving aver-
age from the other or by dividing one
moving average value by the other.
Traditional moving average “crossover”
strategies are extensively relied upon by
traders to discern market direction.
A typical moving average crossover approach, for instance, involves
the calculation of two simple moving averages of different lengths,
such as a 5-day and a 10-day moving average. When the short mov-
ing average value is greater than the long moving average value, the
trend is assumed to be up. When the short moving average value is
less than the long moving average value, the trend is assumed to be
down.
Traditional moving average crossover strategies are quite effective
at filtering out market noise and identifying the current market direc-
tion in trending markets. However, in highly volatile, or choppy, non-
trending sideways markets, or even in trending markets when using
very short moving averages (which may be overly sensitive to short
term price fluctuations), these approaches tend to generate faulty
trading signals. This results in repeated “whipsaws” which can rack
Traditional moving
average crossover
strategies are quite
effective at filtering
out market noise
and identifying the
current market
direction in trend-
ing markets.
64 Trade Secrets
up trading losses as alternating buy and sell signals are triggered each
time the moving averages crisscross one another.
Some trading strategies attempt to reduce the lag by comparing an
actual price, such as the daily close, with a moving average value for
trend determination. Other strategies attempt to minimize whipsaws
by using bands surrounding the moving averages, or by including
additional moving averages to filter out false trading signals, both of
which I implemented in ProfitTaker in the early 1980s. The number
of permutations and combinations of what can be done with moving
averages is staggering.
Figure 4-3 shows the U.S. Dollar Index with its 5-day and 10-day
simple moving averages superimposed on the daily price chart. In
this case, trading decisions might be based on the short moving aver-
age crossing the long moving average (or on the close crossing one
or both of the moving averages). Notice how the turning points in the
moving averages lag behind the turning points in the market itself.
A basic assumption underlying the application of moving averages
is that a trend once in motion tends to persist. Therefore, until the
Figure 4-3. U.S. DOLLAR INDEX
A SIMPLE MOVING AVERAGE CROSSOVER APPROACH
Chart of daily prices of the U.S. Dollar Index with its 5-day and 10-day simple mov-
ing averages shows how short averages are more responsive than long averages,
but both lag behind the market.
Source: VantagePoint Intermarket Analysis Software
5-day moving average
10-day moving average
Trend Forecasting With Technical Analysis 65
long moving average is penetrated by the short moving average, for
instance, in the direction opposite from the prevailing trend, the pre-
vailing trend is assumed to still be intact.
Computing a Simple Moving Average Is Easy
The 5-day simple moving average of closes as of today’s close is
calculated by adding up the values of the most recent five days’ clos-
ing prices and dividing by 5.
Mathematically this involves adding up or “summing” the closing
prices for Day
t
+ Day
t-1
+ Day
t-2
+ Day
t-3
+ Day
t-4
, in which Day
t
is today’s Close, Day
t-1
is yesterday’s Close . . . and Day
t-4
is the Close
of the trading day four days ago. Then the sum is divided by 5.
Figure 4-4 shows a series of five daily closing prices of the Nasdaq
Composite Index and the computation of its 5-day simple moving
average.
This same approach can be used to calculate simple moving aver-
ages of various lengths, such as a 10-day moving average, a 50-day
moving average or a 200-day moving average. Additionally, prices
other than the close can be used in the computation. For instance, a
simple moving average can be computed on the High + Low divid-
ed by 2, or on the Open + High + Low + Close divided by 4. Even
intraday moving averages can be computed for various time intervals.
Figure 4-4. THE NASDAQ COMPOSITE INDEX
CALCULATING A 5-DAY SIMPLE MOVING AVERAGE OF CLOSES
Computing a simple moving average is easy. Just add up the prices and divide by
the number of days.
Source: Market Technologies Corporation
Closing Prices
Day
t-4
3384.73
Day
t-3
3499.58
Day
t-2
3529.06
Day
t-1
3607.65
Day
t
3717.57
____________
17,738.59
17,738.59 –– .
.
5 = 3547.72
= Today’s 5-Day Moving
Average of Closes
66 Trade Secrets
Displaced Moving Averages: Close But “No Cigar”
One intriguing type of moving average that attempts to overcome
the lag effect is the displaced moving average. Ordinarily when com-
puting a moving average and using it as part of a trading strategy, the
moving average value for Day
t
is plotted on a price chart in align-
ment with the closing price of Day
t
.
When this is done the lag is evident visually on the price chart as
the market trends higher, for instance, and the moving average trails
below the most recent prices. Similarly, if the market reverses abrupt-
ly and starts to trend lower, the moving average lags above the most
recent prices and briefly may even continue to increase in value as
the market declines.
A displaced moving average attempts to minimize the lag by “dis-
placing” or “shifting” the moving average value forward in time on the
chart. So, in other words, a 5-day moving average value calculated on
Day
t
(today), instead of being plotted in alignment with the price of
Day
t
, might be shifted forward (to the right) so it is plotted on the
price chart to correspond with Day
t+2
(the day after tomorrow).
Similarly, a 10-day moving average might be shifted forward four days
into the future from today to correspond with Day
t+4
.
The implicit assumption behind displacing a moving average is that
the future period’s actual moving average value (which is yet to be
determined) will turn out to be equal to today’s actual moving aver-
age value. This is, of course, a very simplistic and unrealistic assump-
tion regarding the estimate of the future period’s moving average
value. However, it is, nevertheless, a forecast —not just a linear extra-
polation from past price data such as one achieves by extending a
support or resistance line to the right of a price chart.
A New Way to Forecast Moving Averages
The fact that despite their limitations moving averages continue to
be widely used by traders is testimony that moving averages are rec-
ognized in the financial industry as an important quantitative trend
identification tool. Yet, at the same time, the inherent lagging nature
of moving averages continues to be a very serious shortcoming that
has dogged technical analysts and traders for decades.
Trend Forecasting With Technical Analysis 67
If this deficiency were somehow overcome, moving averages could
rank as the most effective trend identification and forecasting techni-
cal indicator in financial market analysis.
Since traditional moving averages are computed using only past
price data—the price for today, for yesterday, and so on—turning
points in the moving averages will always lag behind turning points
in the market.
For instance, to compute a 5-day simple moving average as of
today’s close, today’s close plus the previous four days’ closes are
used in the computation, as depicted previously in Figure 4-4 (see
page 65). These prices are already known since they have all already
occurred. The problem with this computation, from a practical trad-
ing standpoint, is that the moving aver-
age lags behind what is about to hap-
pen in the market tomorrow.
For a trader trying to anticipate what
the market direction will be tomorrow,
and determine entry and exit points for
tomorrow’s trading, any lag, however
small, may be financially ruinous given
today’s market volatility.
By comparison, a predicted 5-day
simple moving average for two days in
the future, based upon the most recent
three days’ closing prices up through
and including today’s close (which are
known values), plus the next two days’ closing prices (which have
not yet occurred) would have, by definition, no lag, if the exact clos-
ing prices for the next two trading days were known in advance.
Unfortunately, there is no such thing as 100% accuracy when it
comes to forecasting market direction or prices for even one or two
days in advance. No one will ever be able to predict the financial
markets perfectly—not now, not in a hundred years. Through finan-
cial forecasting, though, mathematical expectations of the future can
be formulated.
Needless to say, it is very challenging to predict the market direc-
tion of any financial market. The further out the time horizon, the less
reliable the forecast. That’s why I have limited VantagePoint’s fore-
No one will ever be
able to predict the
financial markets
perfectly—not now,
not in a hundred
years. Through
financial forecast-
ing, though, mathe-
matical expecta-
tions of the future
can be formulated.
68 Trade Secrets
casts to four trading days, which is more than enough lead time to
gain a tremendous trading advantage.
Trying to predict crude oil or the S&P 500 Index a month, six
months or a year from now is impractical from a trading standpoint.
This is due in part to the fact that market dynamics entail both ran-
domness and unforeseen events that are, by definition, unpredictable.
Plus, let’s face it, forecasting is not an exact science; there’s a lot of
“art” involved.
I have successfully applied neural networks to intermarket data in
order to forecast moving averages, turning them into a leading indi-
cator that pinpoints expected changes in market trend direction with
nearly 80% accuracy. This is in sharp
contrast to using moving averages as a
lagging indicator, as most traders still
do, to determine where the trend has
been.
If you are driving down an interstate
highway at seventy miles per hour, you
wouldn’t only look backwards through
your rear window or over your shoul-
der. You need to look forward, out the
front window at the road ahead, so you
can anticipate possible dangers in or-
der to prevent an accident from hap-
pening. It is the same with trading.
An enormous competitive advantage
is realized by being able to anticipate
future price action, even by just a day or two, so you can guide your
trading decisions based upon your expectation of what is about to
happen.
VantagePoint uses price, volume and open interest data on each
target futures market and selected related markets as inputs into its
neural networks. In this manner, its moving average forecasts are not
based solely upon single-market price inputs.
In the case of VantagePoint’s Nasdaq-100
®
program, for example,
the raw inputs into the forecast of the moving averages include the
daily open, high, low, close, volume and open interest for the
Nasdaq-100 Index, plus nine related markets as shown in Figure 4-5.
I have successfully
applied neural
networks to inter-
market data in
order to forecast
moving averages,
turning them into a
leading indicator
that pinpoints
expected changes in
market trend direc-
tion with nearly
80% accuracy.
Similarly, every other VantagePoint program has its own specific re-
lated markets, which provide intermarket input data into its neural
networks.
Leading Indicators Give You a
Competitive Edge
Since identifying the trend direction of a market is so critical to suc-
cessful trading of that market, trend forecasting strategies offer a sub-
stantial competitive advantage over traditional market lagging, trend
following strategies.
I have found that predicted moving averages are most effective for
trend forecasting when they are incorporated into more complex
indicators, such as moving average crossover strategies, which can be
used to identify not only the anticipated direction of the trend but
also its strength. This has been implemented within VantagePoint by
comparing predicted moving averages for certain time periods in the
future with today’s actual moving averages of the same length.
For instance, VantagePoint compares a predicted 10-day moving
average for four days in the future with today’s actual 10-day moving
average calculated as of today’s close. It also forecasts other moving
averages and makes similar comparisons, including that of a pre-
dicted 5-day moving average for two days in the future with today’s
actual 5-day moving average calculated through today’s close.
Trend Forecasting With Technical Analysis 69
Figure 4-5. INTERMARKET DATA USED BY VANTAGEPOINT’S
NASDAQ-100 PROGRAM
VantagePoint’s Nasdaq-100 program analyzes the Nasdaq-100 Index plus nine related
markets to generate intermarket-based forecasts.
Source: Market Technologies Corporation
• Dow Jones Industrial Average
• 30-Year Treasury Bonds
• S&P 500 Index
• U.S. Dollar Index
• S&P 100
®
• NYSE Composite Index
®
• Bridge/CRB Index
• Dow Jones Utility Average
SM
• Light Crude Oil
70 Trade Secrets
Figure 4-6 shows a crossover of the predicted 10-day moving aver-
age and the actual 10-day moving average for the Dow Jones Indus-
trial Average. Notice that the predicted moving average, because it is
being forecasted for four days in advance, does not lag behind the
market, while the actual 10-day moving average lags behind both the
market and the predicted moving average.
The leading indicators within VantagePoint, involving the crossover
of predicted moving averages with actual moving averages, will be
discussed in more detail in the next chapter.
Figure 4-6. DOW JONES INDUSTRIAL AVERAGE
USING A PREDICTED MOVING AVERAGE CROSSOVER STRATEGY
Chart of daily prices of The Dow with a 10-day predicted moving average and 10-day
actual moving average crossover. Notice the difference in lag between the predicted
and actual moving averages.
Source: VantagePoint Intermarket Analysis Software
Predicted 10-day mov-
ing average, forecasted
4 days into the future
Actual 10-day
moving average
VANTAGEPOINT FORECASTS
MARKET DIRECTION
How to Get a Sneak Preview of Where the
Markets Are Going and Use This
Information to Your Advantage
V
antagePoint uses the pattern recognition capabilities of neural
networks to analyze market data from each target market plus
selected related markets in order to make forecasts for that tar-
get market. This is accomplished by predicting short-term moving
averages, which are then used to indicate the market direction of
each target market.
Since 1991 when VantagePoint was first introduced, Market Tech-
nologies Corporation’s research team, the Predictive Technologies
Group, under my direction has continued to conduct proprietary
research and development with neural networks and intermarket
analysis. Updated versions of VantagePoint have been released as
improvements in its forecasting accuracy have been achieved.
VantagePoint Monitors Major Financial Markets
Presently there are twenty-five actively traded financial markets that
VantagePoint monitors each day. These include interest rates, stock in-
dexes, energies and currencies, as presented in Figure 5-1 on page 72.
With its ability to make consistently accurate trend forecasts for
these actively traded financial markets, VantagePoint offers a competi-
tive advantage, from an intermarket perspective, to serious traders in
Trend Forecasting With Technical Analysis 71
Chapter 5
72 Trade Secrets
the futures, options and equity markets. It’s not a crystal ball, but it
may be the next best thing.
Many VantagePoint clients day trade while others position trade or
do a combination of both. Some clients trade full-time while others,
employed outside the financial industry, trade part-time.
Typically VantagePoint is used by traders in conjunction with other
technical trading tools that they are already using. In this way Van-
tagePoint’s predictive indicators act as intermarket confirmation filters
to various single-market indicators that only look internally at each
market.
When VantagePoint confirms these single-market indicators from
an intermarket perspective, that’s a green light to take the trade.
However, when VantagePoint is in disagreement with these single-
market indicators, that’s a bright yellow caution light.
FIGURE 5-1. FINANCIAL MARKETS COVERED BY VANTAGEPOINT
VantagePoint monitors interest rate, stock index, energy and currency markets, giv-
ing intermarket-based forecasts.
Source: Market Technologies Corporation
30-Year T-Bonds
10-Year T-Notes
5-Year T-Notes
2-Year T-Notes
Eurodollar
INTEREST RATES
S&P 500
S&P 100
FTSE 100
Nikkei
Nasdaq-100
Nasdaq Composite
Dow
STOCK INDEXES
Gasoline
Natural Gas
Gas Oil
Brent Crude
Light Crude
Heating Oil
ENERGIES
Swiss Franc
Deutsche Mark
British Pound
Canadian Dollar
Australian Dollar
U.S. Dollar Index
Japanese Yen
CURRENCIES
After spending a little time becoming familiar at first with its reports
and charts, it takes just a few minutes each day to update Vantage-
Point and have its predictive intermarket-based information available
for making your trading decisions.
Figure 5-2 lists the predictive accuracy of VantagePoint’s trend fore-
casts, based on its proprietary Neural Index indicator (which will be
discussed later), for each of the twenty-five financial markets cur-
rently monitored by VantagePoint.
Five Neural Networks Make Independent Forecasts
Each VantagePoint program is specifically designed for a particular
target market and uses five neural networks, in a two-level hierarchy,
to forecast five different leading indicators for that market.
Trend Forecasting With Technical Analysis 73
FIGURE 5-2. PREDICTIVE ACCURACY OF VANTAGEPOINT’S TREND FORECASTS
In the financial markets, 100% predictive accuracy is not attainable. With random-
ness and unforeseen events, perhaps only 80-85% is realistically possible.
30-Year T-Bonds 74.60%
10-Year T-Notes 76.10%
5-Year T-Notes 81.67%
2-Year T-Notes 72.20%
Eurodollar 73.90%
INTEREST RATES
S&P 500 76.60%
S&P 100 78.40%
FTSE 100 74.57%
Nikkei 70.80%
Nasdaq-100 75.40%
Nasdaq Composite 78.56%
Dow 78.09%
STOCK INDEXES
Gasoline 73.00%
Natural Gas 73.70%
Gas Oil 81.33%
Brent Crude 73.67%
Light Crude 76.64%
Heating Oil 70.70%
ENERGIES
Swiss Franc 72.50%
Deutsche Mark 76.02%
British Pound 77.10%
Canadian Dollar 76.67%
Australian Dollar 77.50%
U.S. Dollar Index 76.67%
Japanese Yen 74.66%
CURRENCIES
Source: Market Technologies Corporation
74 Trade Secrets
• The first network forecasts tomorrow’s High, to help set stops for
entry and exit points.
• The second network forecasts tomorrow’s Low, to help set stops for
entry and exit points.
• The third network forecasts a 5-day moving average of closes for
two days in the future, to indicate the expected Short-Term trend
direction within the next two days.
• The fourth network forecasts a 10-day moving average of closes for
four days in the future, to indicate the expected Medium-Term
trend direction within the next four days.
• The fifth network indicates if the market is expected to change
trend direction by making a top or bottomwithin the next two days.
The first four networks at the primary
level of the network hierarchy make in-
dependent market forecasts of the High,
Low, Short-Term trend and Medium-
Term trend. These forecasts are then
used as inputs into the fifth network
along with other target market and inter-
market data inputs, at the secondary
level of the network hierarchy, to predict
market Turning Points. VantagePoint’s
neural network configuration is shown
in Figure 5-3 (see page 75).
While the underlying mathematics behind VantagePoint is very
complex, its forecasted intermarket-based trading information is easy
to understand. Even a new trader with no background in mathemat-
ics or technical analysis can begin to benefit immediately from its
information. VantagePoint is designed for active traders, not engineers
or rocket scientists.
VantagePoint’s forecasts are presented for each target market in a
one-page Daily Report. A more detailed History Report is also avail-
able for more in-depth analysis. VantagePoint’s predictive information
is also exportable to other software programs. Additionally, all of the
indicators presented in the Daily Report can be displayed or printed
as detailed color charts, for traders who are more visually oriented.
Figure 5-4 (see page 76) shows a VantagePoint chart of the Dow
Jones Industrial Average with its predicted 10-day moving average
While the under-
lying mathematics
behind Vantage-
Point is very
complex, its fore-
casted intermarket-
based trading
information is easy
to understand.
and actual 10-day moving average superimposed on the daily prices.
In this example, the entry point to go long occurs when the predict-
ed moving average crosses the actual moving average from below to
above as indicated by the “up arrow” at the left of the chart. The long
position is maintained until the predicted moving average crosses the
actual moving average from above to below as indicated by the
“down arrow” at the right of the chart.
Trend Forecasting With Technical Analysis 75
FIGURE 5-3. VANTAGEPOINT’S FIVE NEURAL NETWORKS
VantagePoint makes five different forecasts for each target market using five sepa-
rate neural networks. There’s a lot of horsepower under the hood, but you don’t have
to be a race-car driver to get your intermarket driver’s license. VantagePoint is de-
signed for traders, not rocket scientists.
Source: Market Technologies Corporation
Network 1
Network 2
Predicted
High
Predicted
Low
Predicted
Short Trend
Predicted
Medium
Trend
Neural
Index
Predicted
Turning
Points
Network 3
Network 4
Network 5
76 Trade Secrets
Figure 5-4. THE DOW JONES INDUSTRIAL AVERAGE
CROSSOVER OF PREDICTED AND ACTUAL MOVING AVERAGES
A simple moving average crossover strategy with a twist —it compares a predicted
10-day moving average with an actual 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
1,155 point trade = $11,550
Predicted 10-day
moving average
Actual 10-day
moving average
Figure 5-5 (see page 77) shows a sample VantagePoint Daily Report
for the Nasdaq Composite Index. Notice that the report is divided into
three sections, each of which will be discussed in detail shortly.
Figure 5-6 (see page 77) shows a sample VantagePoint History
Report for the Nasdaq Composite Index.
The layout, information and interpretation of a VantagePoint chart
or report for one target market are identical to those for each of the
other target markets. Therefore, once you are familiar using Vantage-
Point on one market, it is simple to use it on others. In fact, Vantage-
Point is designed so that it can be updated on all twenty-five markets
automatically at the touch of your mouse button. The whole process
takes just a few minutes each day.
What VantagePoint’s Daily Report Tells You
Each Daily Report gives you intermarket-based forecasts for use on
the next trading day, in addition to information from previous days to
give some background on what has just happened in that market.
FIGURE 5-5. A SAMPLE NASDAQ COMPOSITE DAILY REPORT
VantagePoint’s Daily Report is divided into three sections.
Source: VantagePoint Intermarket Analysis Software
FIGURE 5-6. A SAMPLE NASDAQ COMPOSITE HISTORY REPORT
VantagePoint’s History Report offers more detailed analysis.
Source: VantagePoint Intermarket Analysis Software
78 Trade Secrets
Figure 5-7 displays Section 1 of a VantagePoint Daily Report for the
10-year Treasury notes program.
Section 1 displays the following information:
• Today’s actual Open, High, Low, Close.
• Today’s actual 5-day simple moving average of closes. This is
labeled TrndS (for Trend Short).
• Today’s actual 10-day simple moving average of closes. This is
labeled TrndM (for Trend Medium).
Figure 5-8 (see page 79) displays Section 2 of a VantagePoint Daily
Report for the 10-year Treasury notes program.
Section 2 displays the following information:
• Tomorrow’s predicted High. This is labeled PHigh.
• Tomorrow’s predicted Low. This is labeled PLow.
• Predicted 5-day simple moving average of closes for two days in the
future. This is labeled PTS (for Predicted Trend Short). Three of the
closing prices (today, yesterday and the day before yesterday) are
FIGURE 5-7. 10-YEAR TREASURY NOTES—SECTION 1 OF THE DAILY REPORT
Section 1 of the Daily Report displays the Open, High, Low, Close, actual 5-day and
actual 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
Open High Low Close TrndS TrndM
4/24/00 9816 9840 9812 9816 9806 9819
4/25/00 9816 9816 9732 9734 9802 9808
4/26/00 9732 9754 9730 9736 9763 9802
4/27/00 9734 9748 9646 9654 9744 9759
4/28/00 9656 9712 9630 9662 9728 9750
5/01/00 9660 9702 9644 9646 9708 9739
5/02/00 9646 9656 9626 9628 9658 9730
5/03/00 9626 9638 9558 9562 9638 9718
5/04/00 9600 9608 9532 9536 9621 9701
5/05/00 9540 9562 9512 9518 9600 9646
5/08/00 9518 9534 9460 9500 9542 9625
5/09/00 9460 9520 9456 9516 9526 9610
Actual 5-day
moving average
Actual 10-day
moving average
Trend Forecasting With Technical Analysis 79
FIGURE 5-8. 10-YEAR TREASURY NOTES—SECTION 2 OF THE DAILY REPORT
Section 2 of the Daily Report displays the predicted High, predicted Low, predicted
5-day moving average and predicted 10-day moving average.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
PHigh PLow PTS PTM
4/24/00 9829 9800 9812 9816
4/25/00 9747 9712 9752 9751
4/26/00 9755 9724 9743 9748
4/27/00 9704 9630 9710 9725
4/28/00 9723 9646 9701 9723
5/01/00 9703 9632 9650 9701
5/02/00 9645 9616 9640 9652
5/03/00 9612 9543 9614 9637
5/04/00 9550 9518 9554 9619
5/05/00 9533 9502 9531 9601
5/08/00 9519 9448 9513 9546
5/09/00 9535 9462 9512 9537
Predicted 5-day
moving average
Predicted trading
range for the next day
Predicted 10-day
moving average
known since they have already occurred up through today’s close.
The remaining two closing prices (for tomorrow and the day after
tomorrow) are not known since they have not yet occurred.
• Predicted 10-day simple moving average of closes for four days in
the future. This is labeled PTM (for Predicted Trend Medium), in
which six of the closing prices are known, but the remaining four
closing prices are not known.
Figure 5-9 (see page 80) displays Section 3 of a VantagePoint Daily
Report for the 10-year Treasury notes program.
Section 3 displays the following information:
• The Strength Index, a weighted composite of the four indicators from
Section 2, indicates if the market is getting overbought or oversold.
• PHigh Diff displays the difference between the predicted High for
tomorrow from Section 2, and today’s actual High from Section 1.
• PLow Diff displays the difference between the predicted Low for
tomorrow from Section 2, and today’s actual Low from Section 1.
80 Trade Secrets
• The Neural Index indicates whether or not the market is expected
to make a top or bottom and change trend direction within the next
two days, based on a comparison of two 3-day moving averages.
• PTS Diff displays the difference between the predicted 5-day mov-
ing average for two days in the future (PTS) from Section 2, and
today’s actual 5-day moving average (TrndS) from Section 1.
• PTM Diff displays the difference between the predicted 10-day
moving average for four days in the future (PTM) from Section 2,
and today’s actual 10-day moving average (TrndM) from Section 1.
Intermarket Charts Show You What’s Ahead
VantagePoint has extensive charting capabilities to help you visu-
alize its forecasts of market trend direction and prices. This is really
what makes VantagePoint so unique.
FIGURE 5-9. 10-YEAR TREASURY NOTES—SECTION 3 OF THE DAILY REPORT
Section 3 of the Daily Report displays the Strength Index, differences between the
predicted indicators and today’s actual indicators, and the Neural Index. This sec-
tion alerts you to an impending change in market direction and strength.
Source: VantagePoint Intermarket Analysis Software
VantagePoint Daily Report
10-Year T-Note
Strength PHighDiff PLowDiff Index PTSDiff PTMDiff
4/24/00 -0.36 -11 -12 1.00 6 -3
4/25/00 -0.70 -33 -20 0.00 -14 -21
4/26/00 -0.45 1 -6 0.00 -20 -18
4/27/00 -0.73 -44 -16 0.00 -34 -34
4/28/00 0.15 11 16 0.00 -27 -27
5/01/00 -0.50 1 -12 0.00 -22 -38
5/02/00 -0.69 -11 -10 0.00 -18 -42
5/03/00 -0.72 -26 -15 0.00 -24 -45
5/04/00 -0.72 -22 -14 0.00 -31 -46
5/05/00 -0.72 -29 -10 0.00 -33 -45
5/08/00 -0.71 -15 -12 0.00 -29 -43
5/09/00 0.09 15 6 0.00 -14 -37
PTS Diff becomes negative indicating weakness
Index turns to 0.00
indicating weakness
PTM Diff becomes
more negative
indicating further
weakness
Trend Forecasting With Technical Analysis 81
Unlike traditional charts, VantagePoint’s charts show you where it
expects the market to go next, not just where it has been in the past.
While other traders are still relying solely upon single-market trend
following indicators, which look backward and can only identify
trend changes after the fact, VantagePoint lets you look forward so
you get a sneak preview of what’s ahead. This is like having a road
map that other traders can’t decipher because they don’t know the
secret code.
VantagePoint has two modes of chart presentation: Overlay and
Displaced.
• In Overlay mode, the predicted indicator is plotted on the day that
the prediction is made.
• In Displaced mode, the indicator is plotted on the day for which it
is predicted rather than on the day the prediction is made.
Figure 5-10 displays a VantagePoint chart showing the predicted
10-day moving average of the 10-year Treasury notes plotted in
Overlay mode. This indicator predicts what the 10-day moving aver-
age value will be four days in the future. Notice how turns in the pre-
dicted moving average do not lag behind turns in the market itself.
Figure 5-10. PREDICTED 10-DAY MOVING AVERAGE IN OVERLAY MODE
Chart of daily prices of 10-year Treasury notes with its predicted 10-day moving
average plotted in Overlay mode.
Source: VantagePoint Intermarket Analysis Software
Predicted 10-day
moving average
Figure 5-11 displays a VantagePoint chart showing the next day’s
predicted High and Low of the Dow Jones Industrial Average plotted
in Displaced mode onto the actual day that corresponds to the pre-
dictions. These price forecasts are used by traders to determine entry
and exit points, which will be discussed later in this chapter.
VantagePoint Is Quick and Easy
Each evening after the markets close, that day’s open, high, low,
close, volume and open interest data on each target market and its
nine related markets are downloaded from a VantagePoint-compatible
data vendor’s database or over the Internet. When you perform the
Daily Update function within VantagePoint this information is auto-
matically processed by VantagePoint’s five neural networks which
then generate their forecasts for the next day’s trading.
All you have to do is compare the Daily Reports (or charts) for sev-
eral target markets to one another, to see which markets offer the best
trades to take the next day. The process takes only a few minutes
from start to finish. If there is not a clear-cut indication of market
direction, you would pass on taking a trade in that particular market.
82 Trade Secrets
Figure 5-11. PREDICTED HIGH AND LOW IN DISPLACED MODE
Chart of Dow Jones Industrial Average with its predicted High and Low plotted in
Displaced mode on the actual day that corresponds to the predictions.
Source: VantagePoint Intermarket Analysis Software
Predicted High
Predicted Low
Trend Forecasting With Technical Analysis 83
Only those trades with the highest probability of success should be
taken. This stacks the odds in your favor.
Let’s look at the steps to follow in determining whether or not a
trade is worth taking.
How to Find a Good Trade
The Neural Index in Section 3 of the Daily Report is a good place
to start to get an indication of the expected market trend direction.
The Neural Index is a proprietary indicator, determined by compar-
ing two 3-day moving averages to one another:
• Today’s actual 3-day moving average,
which is the sum of today’s close
(Day
t
), yesterday’s close (Day
t-1
) and
the close of the day prior to yester-
day’s close (Day
t-2
) divided by 3.
• A predicted 3-day moving average,
which is the sum of today’s close
(Day
t
), tomorrow’s close (Day
t+1
)
and the close of the day after tomor-
row (Day
t+2
) divided by 3.
The forecast of the predicted 3-day
moving average is made by Vantage-
Point’s fifth neural network, using pre-
dictions from the other four networks as
inputs, in addition to data from the tar-
get market itself and the specific related
markets pertaining to that target market.
When the predicted 3-day moving average value is greater than
today’s actual 3-day moving average value, the Neural Index is 1.00.
This indicates that VantagePoint expects the market to move higher
over the next two days.
When the predicted 3-day moving average value is less than today’s
actual 3-day moving average value, the Neural Index is 0.00. This indi-
cates that the market is expected to move lower over the next two
days.
With an overall predictive accuracy rate of nearly 80% as indicated
in Figure 5-2 (see page 73), the Neural Index will give you added
The Neural Index in
Section 3 of the
Daily Report is a
good place to start
to get an indication
of the expected
market trend direc-
tion. The Neural
Index is a propri-
etary indicator,
determined by com-
paring two 3-day
moving averages to
one another.
84 Trade Secrets
confidence to pull the trigger when there is a strong indication that a
market is about to make a top or bottom and poised to change trend
direction.
Here’s How to Get Added Confirmation
You can use the PTS Diff and the PTM Diff indicators in Section 3
of the Daily Report in conjunction with the Neural Index to confirm
the expected market direction. The strongest confirmation occurs
when the Index, PTS Diff and PTM Diff are in agreement with each
other.
Each day as VantagePoint’s neural networks are updated with the
most recent data on the target market and its related markets, Van-
tagePoint makes its forecasts and calculates the difference in value
between each predicted moving average and the actual moving aver-
age of the same length. By using forecasted moving averages, Van-
tagePoint retains all of the smoothing effects of moving averages,
while effectively eliminating the lag.
When the predicted moving average crosses above the actual mov-
ing average (the PTS Diff or PTM Diff turns positive), VantagePoint
expects the market trend to turn up within the forecast time horizon
related to each of these two indicators.
• When the PTS Diff is positive, reaches a maximum positive value
and narrows (indicating that the upward trend is beginning to lose
strength), this gives you an early warning that the market is about
to make a top and turn down within the next two days.
• When the PTM Diff is positive, reaches a maximum positive value
and narrows (indicating that the upward trend is beginning to lose
strength), this gives you an early warning that the market is about
to make a top and turn down within the next four days.
Similarly, when the predicted moving average crosses below the
actual moving average (the PTS Diff or PTM Diff turns negative),
VantagePoint expects the market trend to turn down within the fore-
cast time horizon related to each of these two indicators.
• When the PTS Diff is negative, reaches a maximum negative value
and narrows (indicating that the downward trend is beginning to
lose strength), this gives you an early warning that the market is
about to make a bottom and turn up within the next two days.
• When the PTM Diff is negative, reaches a maximum negative value
and narrows (indicating that the downward trend is beginning to
lose strength), this gives you an early warning that the market is
about to make a bottom and turn up within the next four days.
Rather than wait for the crossover to actually occur, you can make
trading decisions based on the narrowing in the PTS Diff or PTM Diff,
which is the earliest warning that the market trend is beginning to lose
strength. For instance, if you are in a long position, you can act on this
information in a number of ways depending on your account size, risk
propensity, information derived from
single-market technical indicators that
you also utilize, your trading style and
objectives. Here are just three possible
strategies that can be implemented:
• If the PTS Diff or PTM Diff reaches a
maximum positive value and narrows
by even a small amount, you can
close out your long position and
stand aside. Then you can wait for
either the PTS Diff or PTM Diff to nar-
row further or wait for one or both of
them to turn negative before taking a
short trade, even if the Neural Index
has still not changed to 0.00. If either
the PTS Diff or PTM Diff (or both)
instead show renewed strength (the
difference between the predicted and
the actual moving average value
widens again instead of continues to narrow), you could re-enter
your long position.
• If the PTS Diff or PTM Diff reaches a maximum positive value and
narrows by even a small amount and the Index is 1.00, you can
tighten your stop and stay in your long position. With this strategy
you are still long should the market show renewed strength. If,
instead, the difference continues to narrow on subsequent days,
you would close out your long position and stand aside or reverse
positions.
• If the PTS Diff or PTM Diff reaches a maximum positive value and
narrows by a predetermined minimum amount, you can close out
Trend Forecasting With Technical Analysis 85
You can use the
PTS Diff and the
PTM Diff indicators
in Section 3 of the
Daily Report in
conjunction with
the Neural Index
to confirm the
expected market
direction. The
strongest confirma-
tion occurs when
the Index, PTS Diff
and PTM Diff are in
agreement with
each other.
86 Trade Secrets
your long position and go short, even if the Index has still not
changed to 0.00. This strategy is the most aggressive of the three
since it involves reversing positions at the earliest indication that the
current market trend is likely to make a top and change direction.
Likewise, if you are short you would wait for the PTS Diff or PTM
Diff to reach a maximum negative value and narrow before follow-
ing one of these three strategies.
To the extent that the PTS Diff and PTM Diff behave similar to each
other from one day to the next (and are confirmed by the Neural
Index), you can be more confident that the market will move as
expected within the forecast time horizons of these three indicators.
By creating trend forecasting strategies, which compare predicted
moving averages with actual moving averages, you can get an early
warning of an impending change in trend direction—days before it
would show up on a traditional price chart or be identified by single-
market trend following indicators such as lagging moving average
crossover approaches.
Here’s a Simple Example
Figure 5-12 is an example
of a 10-year Treasury notes
trade. In practice, each day
after you update Vantage-
Point you would see the lat-
est Index, PTS Diff and PTM
Diff values in Section 3 of
that day’s Daily Report.
For the purpose of this
example, the more conserva-
tive trading strategy of wait-
ing for the Index to change
from 1.00 to 0.00, and for the PTS Diff and PTM Diff to both turn neg-
ative before entering a short trade will be examined. Therefore the
following relatively stringent conditions, which indicate that the mar-
ket is likely to make a top and that weakness is about to set in, will
need to be met:
• If the Index value is 1.00 indicating that the market is in an up
trend, you would wait for the Index to change to 0.00.
Figure 5-12. VANTAGEPOINT PREDICTS A
MARKET TOP AS MARKET
SHOWS STRENGTH
Changes in the Index, PTS Diff and PTM Diff
over a five-day period warn that the market
is about to make a top and turn down.
Source: Market Technologies Corporation
Index PTS Diff PTM Diff
4/24/00 1.00 6 -3
4/25/00 0.00 -14 -21
4/26/00 0.00 -20 -18
4/27/00 0.00 -34 -34
4/28/00 0.00 -27 -27
• If the PTS Diff is positive indicating that the market is in an up trend,
you would wait for the PTS Diff to narrow and turn negative.
• If the PTM Diff is positive indicating that the market is in an up trend,
you would wait for the PTM Diff to narrow and turn negative.
After the close on 4/24/00 VantagePoint reported an Index value of
1.00, a PTS Diff of 6, and a PTM Diff of –3. While the market showed
strength, with progressively higher highs and higher lows on 4/19/00,
4/20/00 and 4/24/00, the negative PTM Diff on 4/24/00 is the first
clear cut confirmation that the market is expected to weaken and turn
down.
After the close on 4/25/00, the Index changed from 1.00 to 0.00
and the PTS Diff changed from 6 to –14, confirming the weakness
that was indicated on 4/24/00 by the negative PTM Diff. In fact, on
4/25/00 the PTM Diff indicated even
further expected weakness, as it
changed from –3 to –21. When these
three leading indicators confirm each
other like this, it is a strong indication
that a short position can be taken. The
expectation of impending weakness
was reaffirmed after the close on
4/26/00, when the Index remained at
0.00 and the PTS Diff changed from -14
to –20.
Once the Index changes from 1.00 to
0.00 and the PTS Diff and PTM Diff
change from positive to negative, fur-
ther weakness is indicated on subse-
quent days if the Index remains at 0.00 and the PTS Diff and PTM
Diff become even more negative. This is what happened after the
close on 4/27/00, when the Index remained at 0.00 and both the PTS
Diff and PTM Diff changed to -34 in value.
The opposite scenario suggests taking a long position. This hap-
pens when the Index changes from 0.00 to 1.00 and the PTS Diff and
PTM Diff are negative and start to narrow by getting less negative,
before changing to positive values. For even more confirmation, the
Strength Index can be used to determine the extent to which the mar-
ket is getting overbought (large positive values) or oversold (large
negative values).
Trend Forecasting With Technical Analysis 87
By creating
trend forecasting
strategies, which
compare predicted
moving averages
with actual moving
averages, you
can get an early
warning of an
impending change
in trend direction.
88 Trade Secrets
Day and Position Trading With Tomorrow’s
Price Forecasts
Once you have identified the expected trend direction using the
Index, PTS Diff and PTM Diff from Section 3 of the Daily Report, you
can set your entry point, by looking at the next day’s predicted High
and predicted Low in Section 2 of the Daily Report. These price fore-
casts create an expected trading range for the next day, which is anal-
ogous to extending support and resistance lines in traditional single-
market technical analysis approaches.
The advantage of VantagePoint, though, is that the next day’s High
and Low forecasts, based on the pattern recognition capabilities of
neural networks applied to intermarket data, are objectively deter-
mined and are not just an arbitrary linear extrapolation from past sin-
gle-market data.
If you are a day trader, you can use the forecasts of the next day’s
High and Low to identify low-risk day trades. If the Neural Index and
forecasted moving average indicators for a specific target market indi-
cate that the next day is expected to be a down day, you can wait for
the market to trade up toward the predicted High before initiating a
short position with a limit or market order, with the intention of clos-
ing out the trade near the predicted Low.
The left side of Figure 5-13 (see page 89) displays the forecast
made after the close on 4/25/00 for the High on 4/26/00 to be 9747
for 10-year Treasury notes. VantagePoint also forecasted this market
to go down on 4/26/00, indicating that day traders can enter short
positions near the predicted High. The right side of Figure 5-13 shows
what actually happened on 4/26/00.
Similarly, long positions can be entered near the predicted Low on
a day expected to be up, with exits near the predicted High. This
allows day traders to sell rallies within an expected downtrend or buy
dips within an expected uptrend, one or more times daily depending
on the intraday market volatility. The profitability of day trades that
are executed with this strategy can be substantial with minimal risk,
since tight stops can be utilized.
If you are a position trader, you can use the forecasts of the next
day’s High and Low to enter positions, then use the subsequent days’
forecasts to move your stop or exit the trade. For example, let’s say
it’s 4/25/00 and you just looked at tonight’s Daily Report and every-
thing indicates a bearish bias for the next day. You decide you want
to go short on 4/26/00. You
can determine where you
should enter the market by
looking at the predicted
High for 4/26/00, as shown
on the Daily Report of
4/25/00 in Figure 5-14. In
this case you could enter a
short position at or near
9747.
Stop Placement Based on Forecasts Not Hunches
You could put a protective buy stop somewhere above the pre-
dicted High of 9747 depending on your risk propensity so your stop
is sufficiently outside of the daily range that VantagePoint forecasts
for 4/26/00. This would lessen the probability of being stopped out
Trend Forecasting With Technical Analysis 89
Figure 5-13. DAY TRADERS USE VANTAGEPOINT’S PRICE FORECASTS
FOR QUICK TRADES
VantagePoint forecasts this market to go down on 4/26/00. Day traders can enter a
short position near the predicted High of 9747, covering the short before the end of
the day.
Source: Market Technologies Corporation
4/25/00
? VantagePoint forecasts the market
to go down on the next day
(4/26/00).
? VantagePoint forecasts the High
on the next trading day (4/26/00)
to be 9747.
? Traders should look to go short
near 9747.
Open:
9732
Low: 9730
Close: 9736
High: 9754
Predicted
High: 9747
Generated on
4/25/00 for trading
on 4/26/00.
4/26/00
Figure 5-14. PREDICTED HIGH AND LOW
IN SECTION 2
Position traders can enter short positions
near the predicted High, and stay in the
position until the market is expected to
make a bottom.
Source: Market Technologies Corporation
PHigh PLow
4/25/00 9747 9712
90 Trade Secrets
prematurely due to intraday market volatility, yet protect you in the
event the market penetrates the predicted High and breaks out to the
upside.
The benefit of setting your stop based on forecasts of the next day’s
High or Low is that your stop is less likely to be clustered among
other traders’ stops which are typically set through traditional meth-
ods of single-market analysis such as extending support and resis-
tance trend lines.
As a position trader you would stay in your short position until the
following day. Then if VantagePoint indicates continued expected
weakness on the Daily Report updated after the close of 4/26/00 (to
be used for trading on 4/27/00), you would hold the short position
for another day. In this case the market opened at 9734 on 4/27/00
and ended up closing substantially lower at 9654 as shown previously
in Figure 5-7 (see page 78). In fact, from Figure 5-9 (see page 80) you
can see that the Index, PTS Diff and PTM Diff all indicated sustained
weakness through 5/8/00 as Treasury notes moved lower by nearly
three points.
Other Markets Give Added Confirmation
Since the neural networks for each VantagePoint program have
been developed and trained independently for each particular target
market, daily reports from other target markets can be used for addi-
tional confirmation.
Once you are familiar with one Daily Report, and understand what
to look for in terms of the PHigh, PLow, Neural Index, PTS Diff and
PTM Diff, it is simple to understand the Daily Reports for other mar-
kets monitored by VantagePoint.
The eurodollar, 2-year Treasury notes, 5-year Treasury notes and
the 30-year Treasury bonds daily reports, for example, add consider-
able insight into what is likely to happen to 10-year Treasury notes,
since these five markets taken together encompass the entire interest
rate yield curve from ninety days to thirty years.
The more the forecasted indicators on these other reports confirm
the indicators on the 10-year Treasury notes Daily Report, the higher
the probability that the Treasury notes market will act as expected.
On the other hand, if these other reports give contrary indications,
you should be cautious. Similar confirmations or divergences can be
found among the energy markets, stock indexes and currencies mon-
itored by VantagePoint.
Even traders who do not trade futures but only buy and sell indi-
vidual stocks (such as new economy technology stocks comprising
the Nasdaq Composite Index or old economy stocks comprising The
Dow) can use VantagePoint’s Nasdaq and Dow programs for timing
individual stock transactions.
How To “Cherry-Pick” the Best Trades to Take
With VantagePoint programs covering major financial markets,
traders with multiple programs can pick only those trades to take
each day that have the highest probability of being profitable. I call
this “cherry-picking.” This lets you avoid the trap that many other
traders fall into, in which they feel compelled to trade even when
there isn’t a good trade to be taken. So they chase after marginal
trades, with predictably negative results.
If you can appreciate the advantage of having intermarket-based
trend forecasts with nearly 80% accuracy at predicting short-term
market direction, and the benefit of broadening your perspective of
the markets beyond simply focusing on the internal dynamics within
each individual market, then you will become a believer in intermar-
ket analysis and the power of neural networks as a market forecast-
ing tool.
In the next chapter I will explain very briefly in non-mathemati-
cal terms what neural networks are and how they can be utilized as
a forecasting tool to predict the market direction of any financial
market.
Trend Forecasting With Technical Analysis 91
NEURAL NETWORKS
How to Raise Your Financial IQ to
Stay Ahead of the Competition
T
he human brain is composed of hundreds of billions of cells
known as neurons, which through their connections to each
other relay information from one neuron to another. This pro-
cess allows a person to learn relationships, draw inferences, recog-
nize patterns and make predictions, among other tasks. While sub-
stantially less complex than the human
brain, neural networks model how it
processes information and performs
pattern recognition and forecasting.
Neural networks are comprised of
individual neurons organized in layers
and interconnected through network
architecture with variable mathematical
weights attributed to each connection.
The architecture includes an input layer,
hidden layer and an output layer.
Neural networks are excellent at sift-
ing through enormous amounts of seem-
ingly unrelated market data and finding
repetitive patterns that could never be
perceived visually just by looking at
price charts or by comparing two markets to one another. Through a
mathematical error minimization process known as “learning” or
“training,” neural networks, if designed properly, can be trained to
make highly accurate market forecasts based upon these patterns.
Trend Forecasting With Technical Analysis 93
Chapter 6
Neural networks
are excellent at
sifting through
enormous amounts
of seemingly unre-
lated market data
and finding repeti-
tive patterns that
could never be
perceived visually
just by looking at
price charts or by
comparing two mar-
kets to one another.
FIGURE 6-1. VANTAGEPOINT’S NEURAL NETWORKS MAKE MARKET FORECASTS
Source: Market Technologies Corporation
94 Trade Secrets
Neural Networks Combine Technical and
Intermarket Data
VantagePoint’s neural networks are designed and trained to make
specific forecasts for each target market. The raw input data from the
target market and related markets, statistical “preprocessing” of the
raw data, network architecture, as well as the training and testing reg-
imens are tailored to each target market.
Figure 6-1 depicts how single-market technical data from a target
market and intermarket data from related markets are fed into
VantagePoint’s neural networks to make predictions for each of the
twenty-five target markets that VantagePoint monitors each day.
Like back-testing and optimization a decade earlier, neural net-
works at first had their skeptics and detractors in the financial indus-
try in the early 1990s, around the time the first version of Vantage-
Point was released. Software developers from outside of the financial
industry, knowledgeable about neural networks applied to other are-
nas and perceiving a potentially lucrative marketplace for their soft-
ware among traders, flooded into the financial industry offering an
assortment of neural network software programs to traders. Before
long neural networks were being hyped in promotional marketing lit-
erature as the Holy Grail of technical analysis as expectations about
their potential reached dizzying heights.
Single-market technical data and intermarket data from related markets are fed into
VantagePoint’s neural networks to make forecasts for the target market.
Data From
Target Market
Data From
Related
Markets
Neural
Networks
Goal
Trend
Forecasts
and
Price
Forecasts
Unfamiliar with the intricacies of the financial markets and the
details underlying technical analysis, many of these newcomers to the
financial industry helped foster a backlash against neural networks
among traders as the Holy Grail remained elusive.
My focus, though, since the mid-1980s has been intermarket analy-
sis. Neural networks just happen to be the best mathematical tool that
I have identified for finding hidden patterns and relationships in
seemingly disparate market data and making highly accurate short-
term market forecasts in a non-subjective, quantitative manner. Neural
networks are not a magic bullet. They are the means, not the end.
Neural Networks Learn Patterns and Make
Forecasts
Over the past decade since first appearing on the financial indus-
try scene, neural networks have been applied successfully to finan-
cial forecasting, corporate decision-making (including risk analysis
and fraud detection), character recognition and medical diagnostics,
to name a few application areas.
Recently with prominent software companies developing and pro-
moting neural network software for decision analysis such as Com-
puter Associates International’s Neugents
™
software, neural networks
have become more accepted as a mainstream mathematical tool.
The Input Layer
A neural network is not limited to single-market technical data
inputs. A neural network is excellent at applying intermarket data (as
well as fundamental data) to market forecasting.
For instance, for a neural network designed to forecast New York
Light Crude Oil, the analysis includes ten years of past price, volume
and open interest data on crude oil futures.
The analysis also includes the following intermarket inputs: crude
oil cash, the Bridge/CRB Futures Price Index, the S&P 100, Comex
gold, Comex silver, the Japanese yen, N.Y. heating oil #2, Treasury
bonds and the U.S. Dollar Index. Additionally, fundamental data in-
puts can be incorporated. Once the raw input data has been select-
ed, it is preprocessed using various algebraic and statistical methods
of transformation, in order to facilitate learning.
Trend Forecasting With Technical Analysis 95
96 Trade Secrets
The Hidden Layer
The hidden layer is used by a neural network for internal process-
ing to store its “intelligence” during the learning process. This layer is
composed of neurons where the network recodes the input data into
a form that captures hidden patterns and relationships. The network
generalizes from previously learned facts to new inputs, which allows
it to make its forecasts. The number of neurons in the hidden layer
and the number of hidden layers are determined through experi-
mentation.
The Output Layer
The output layer is where a network’s forecasts are made. Two
types of real number outputs in financial analysis include forecasts of
prices such as the next day’s high and low, and forecasts of technical
indicators such as a predicted 5-day moving average value for two
days in the future. Decisions must be made about not only what out-
put to forecast, but also how far into the future to make the forecast.
Learning Algorithms
There are many different learning algorithms that can be used to
train a neural network. Each algorithm has different performance
characteristics. All of the algorithms attempt to minimize the overall
error in the network’s forecasts.
One popular learning algorithm is the gradient-descent algorithm.
However, gradient-descent trains slowly and often finds sub-optimal
solutions. This limitation is similar to pitfalls encountered with back-
testing and optimization of rule-based trading strategies in which sub-
optimal sets of parameter values are found that are isolated and
unstable.
How a Neural Network Learns
Training a neural network involves a repetitive mathematical
process in which the neural network learns underlying hidden pat-
terns, discerns leads and lags and identifies nonlinear relationships
within the data from repeated exposures to the input data. Learned
information is stored by the network in the form of a weight matrix,
with changes in the weights occurring as the network “learns.” Similar
to the learning process people engage in, a neural network learns
patterns by being exposed to repeated examples of them. Then the
neural network generalizes through the learning process to related
but previously unseen patterns.
One popular network paradigm that has been used for financial
market analysis and forecasting is known as a “feed-forward” network
that trains through “back-propagation of error” which is depicted in
Figure 6-2.
Once trained, a neural network acts as a market forecasting tool,
allowing traders to achieve the trend identification and forecasting
goals of technical analysis.
Trend Forecasting With Technical Analysis 97
FIGURE 6-2. SIMPLE FEED-FORWARD BACK-PROPAGATION NEURAL NETWORK
Source: Market Technologies Corporation
A simple feed-forward back-propagation network, using technical and intermarket
data as inputs, trains by back-propagation of error throughout the network.
Trend Forecasts
Back
Propagation
of Error Output
Hidden
Input
Input Data From Target Market and
Related Markets
98 Trade Secrets
Overtraining Is Not Desirable
Overtraining a neural network must be avoided. Overtraining
occurs when a neural network memorizes the subtleties and idio-
syncrasies particular to specific training data, without developing the
capacity to generalize to new data. Overtraining is analogous to
curve-fitting or over-optimization when performing back-testing and
optimization on rule-based trading strategies. An overtrained network
will perform poorly on out-of-sample test data and subsequently
when making its forecasts during realtime trading.
How a Neural Network Is Tested for Accuracy
Testing is performed by creating an independent test file made up
of data that had not been seen by a neural network during the train-
ing process. In the testing mode the neural network is given these
new inputs and utilizes the representation that it had previously
learned to generate its forecasts. This allows the network to be eval-
uated under simulated trading conditions. This is analogous to “walk-
forward” or “out-of-sample” testing of rule-based trading strategies.
Performance results from various neural networks on test data can
be compared prior to making a determination about which specific
neural network to select for use in the final application. Depending
on the comparative test performance results, changes often need to
be made in the selection of input data, preprocessing, network archi-
tecture, etc., and retraining conducted before the final application
network is selected.
There’s More to Neural Networks
There are similarities and differences between designing and train-
ing a neural network and developing and testing rule-based trading
strategies. If you want to learn more about the technical details and
underlying mathematics behind neural networks, I refer you to my
personal website www.FutureForecasts.com which includes reprints
of many of the research articles and book chapters I have previous-
ly written about the application of neural networks to technical analy-
sis and market forecasting.
THE NEXT HORIZON
Where Do We Go From Here and
What Does This Mean for Traders?
A
s the world’s financial markets become increasingly integrat-
ed, intermarket analysis will play a crucial role in market
analysis in the first decades of the 21st century, just as back-
testing and optimization of single-market trading strategies became
integral to computerized technical analysis in the late 20th century.
The narrow single-market approach that analyzes each individual
market based upon its own internal past price data must be sup-
planted by a multi-dimensional approach. A decade ago I referred
to the synthesis of technical, intermarket and fundamental ap-
proaches as “synergistic market analysis.” No financial market is an
island. They are now all integrally linked to one another.
Fortunately, neural networks are not only well-suited to analyzing
markets from both a single-market as well as an intermarket per-
spective, but can also incorporate fundamental data inputs. These
might include supply and demand statistics, and economic data
such as the Gross National Product, the Producer Price Index, the
Consumer Price Index and Unemployment statistics. Even compar-
ative economic statistics from different countries can be included.
In effect, as the financial markets continue to evolve, technical
analysis, intermarket analysis and fundamental analysis will blend
together, creating the three-legged stool known as financial market
analysis.
By utilizing the computational modeling capabilities of neural net-
works in a structured framework that integrates seemingly disparate
Trend Forecasting With Technical Analysis 99
Chapter 7
100 Trade Secrets
technical, intermarket and
fundamental data as depict-
ed in Figure 7-1, quantita-
tive trend forecasting will
continue to be at the cut-
ting-edge of financial market
analysis in the 21st century.
History is replete with ac-
counts of newly emerging
technologies, which have
subsequently had a major
impact on economic devel-
opment and the financial
markets —making early a-
dopters wealthy in the
process. The railroad, the air-
plane, the telephone, xerog-
raphy, and the Internet rep-
resent such technologies,
with substantial commercial
applications, which have
become part of the econom-
ic landscape.
Technological progress cannot be forestalled by those who are skep-
tical, inflexible or simply too afraid to adopt something new or differ-
ent. Such close-mindedness and shortsightedness is an anachronism
in today’s rapidly changing technology-driven world.
Within the financial industry, the same can be said for the applica-
tion of advanced quantitative technologies such as neural networks
and intermarket analysis to global financial market analysis and trad-
ing. In the past, new analytical innovations involving the application
of quantitative technologies have met resistance within the financial
industry. In the future, though, as emerging technologies demonstrate
their effectiveness they will become more quickly incorporated into
the practice of financial market analysis.
Neural networks are real; they work, and they are here to stay. Still,
they are just one of the mathematical tools applicable to the imple-
mentation of synergistic trading strategies. Other tools, including ex-
pert systems, genetic algorithms, fractal geometry, chaos theory and
FIGURE 7-1. SYNERGISTIC ANALYSIS
LOOKS AT THE BIG PICTURE
Source: Market Technologies Corporation
The next phase in the evolution of technical
market analysis will be “synergistic market
analysis,” combining technical, intermar-
ket and fundamental data. This completes
the three-legged stool of financial market
analysis, covering the entire global eco-
nomic and financial landscape.
Technical
Data
Fundamental
Data
Intermarket
Data
fuzzy logic to name a few, are also being applied to market analysis
with varying degrees of success. There is certainly much more to
come!
There Will Never Be a Financial Crystal Ball
My research and development efforts will continue to be focused
on increasing VantagePoint’s forecasting accuracy. Some of the factors
that are under study involve the inclusion of additional global mar-
kets to be considered as intermarket inputs and the optimization of
the size of the moving average lengths and look-forward periods that
are used to make the trend forecasts.
In addition, I intend to develop additional VantagePoint programs
to monitor financial markets outside of the United States such as
Short Sterling on the London International Financial Futures Ex-
change and the Euroyen on the Singapore Exchange Ltd. I am also
interested in applying intermarket analysis to individual large-cap
equities comprising the Nasdaq-100 Index and assessing the impact
of incorporating fundamental data inputs into VantagePoint.
Obviously, there will never be a financial crystal ball that traders
can gaze into to see what the markets will do in the future with 100%
accuracy. In my opinion it will not be possible for market analysts to
predict trend direction with more than 80-85% accuracy, due to ran-
domness and unpredictable events that are inherent in the global
financial markets, as well as the difficulty of developing effective fore-
casting tools.
With VantagePoint’s current accuracy level over 70% on all twenty-
five markets monitored, over 75% on fourteen of them, and over 80%
on two of them (the 5-year Treasury notes and gas oil), VantagePoint
is already within striking distance of what is realistically attainable in
terms of forecasting accuracy.
Even then, there are a myriad of additional factors such as mass psy-
chology, judgment, trading experience, risk propensity, fear, greed,
money management and amount of capital that affect one’s trading
performance.
I am determined to push the forecasting envelope as far as it will
go. It’s my passion. This is what has made the financial markets and
Trend Forecasting With Technical Analysis 101
102 Trade Secrets
technical analysis so emotionally exciting, intellectually challenging
and financially compelling to me.
Right now, a robust, yet easy-to-use, intermarket analysis tool such
as VantagePoint is a smart way for serious traders to fill the gap in
their technical analysis arsenals so they can start benefiting immedi-
ately from intermarket analysis without having to reinvent the wheel
or study to become rocket scientists.
As more traders embrace intermarket analysis and incorporate it
into their trading, they will be able to make winning market trades
based on the hidden relationships and complex patterns between
related markets, reflecting the market synergy behind today’s global
markets.
I hope that this book has helped make you more aware of the
implications that the globalization of the financial markets has on
your own trading, and am confident that by broadening your per-
spective to include intermarket analysis, whether you are a stock,
options or futures trader, you will be able to improve your trading
performance and self-confidence to make more decisive and prof-
itable trading decisions.
If you have any questions concerning any of the information cov-
ered in this book, please feel free to contact Market Technologies
Corporation by e-mail at [email protected] or through its website
at www.ProfitTaker.com where you can learn more about intermarket
analysis, neural networks and VantagePoint.
At the website, you can also examine actual up-to-date Vantage-
Point Daily Reports for various financial markets, which will show
you in more detail how VantagePoint can benefit you. Additionally,
you can register on the website to receive free e-mail alerts from
Market Technologies Corporation. You can also contact Market Tech-
nologies Corporation by telephone at 800-732-5407 or 813-973-0496
or by fax at 813-973-2700.
Trading
Resource
Guide
? ? ? ? ? ?
TOOLS FOR SUCCESS
IN TRADING
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Trend Forecasting With Technical Analysis 105
106 Trade Secrets
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Trend Forecasting With Technical Analysis 107
108 Trade Secrets
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Learn More About
VantagePoint Software
Trend Forecasting and Market Timing Technology
? ? ? ? ? ?
Discover how you can stack the odds in your
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I
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Trend Forecasting With Technical Analysis 113
ties, each day you’ll know—with
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TM
114 Trade Secrets
Industry Pros, Real Traders,
and Product Reviewers are Raving about
VantagePoint
? ? ? ? ? ?
“Louis Mendelsohn was the first person to develop intermarket analy-
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Trend Forecasting With Technical Analysis 115
About the Author and
Market Technologies
Corporation
? ? ? ? ? ?
Louis B. Mendelsohn is president and chief executive officer of
Market Technologies Corporation. Mr. Mendelsohn began trading
equities in the early 1970s, followed by stock options. Then, in the late
1970s he started trading commodities, as both a day and position trad-
er. In 1979, he formed Market Technologies Corporation to develop
technical analysis trading software for the commodity futures markets.
In 1983, Mendelsohn pioneered the first commercial strategy back-
testing and optimization trading software for microcomputers. By the
mid-1980s these capabilities became the standard in microcomputer
trading software for both equities and futures, fueling the growth of
today’s multi-million dollar technical analysis software industry.
Recognizing the emerging trend toward globalization of the
world’s financial markets, in 1986 Mr. Mendelsohn again broke new
ground in technical analysis when he introduced the first commer-
cial intermarket analysis software in the financial industry for micro-
computers.
Building on his extensive research in the 1980s involving intermar-
ket analysis, in 1991 Mendelsohn released VantagePoint Intermarket
Analysis Software, which makes short-term market forecasts based
upon the pattern recognition capabilities of neural networks. Since
then, Mendelsohn’s research has continued to focus on intermarket
analysis and market forecasting. In addition to his research, software
development and corporate management responsibilities, he actively
trades in the financial markets.
Mr. Mendelsohn has written extensively since 1983 in many promi-
nent financial publications including Barron’s
®
, Futures, and
Technical Analysis of Stocks & Commodities
™
. He has been widely
quoted in the financial media including The Wall Street Journal and
Investor’s Business Daily, has collaborated on more than half a
dozen books on technical analysis, and has been interviewed live on
national radio and television, including CNBC.
Mendelsohn has also spoken at numerous financial conferences
and symposia, including the Futures Industry Association annual
meeting, Futures Symposium International, the Harvard Business
School Alumni Club, Futures Truth and the Annual Meeting of the
Association for Investment Management and Research.
Due to his achievements in the application of computers and
information technologies to technical analysis over the past quarter-
century, his biography is included in Marquis Who’s Who in the
World
®
, Who’s Who in America
®
, and Who’s Who in Finance and In-
dustry
®
. He has been a full member of the Market Technicians Asso-
ciation since 1988, and is a colleague of the International Federation
of Technical Analysts.
Born in 1948 in Providence, Rhode Island, Mendelsohn received a
B.S. degree in Administration and Management Science from
Carnegie Mellon University in 1969, an M.S.W. degree from the State
University of New York at Buffalo in 1973, and an M.B.A. degree
with Honors from Boston University in 1977.
Since its founding by Mr. Mendelsohn, Market Technologies Cor-
poration has been at the forefront of development of state-of-the-art
technical analysis tools and information technologies for the finan-
cial markets. Located in the Tampa Bay region of Florida since 1979,
the firm has individual and institutional clients in over thirty coun-
tries throughout the world.
Market Technologies Corporation was recently ranked the 29th
fastest growing private corporation in Florida, out of the top one-hun-
dred companies in the Florida 100 competition based on three-year
revenue growth, sponsored by the University of Florida, Deloitte &
Touche LLP, PricewaterhouseCoopers LLP, and Raymond James &
Associates, Inc.
116 Trade Secrets
Trend Forecasting With Technical Analysis 117
Market Technologies Corporation was also ranked the 17th fastest
growing technology company in Tampa Bay, based on five-year rev-
enue growth, out of the top fifty public and private technology firms
in the Tampa Bay Technology Fast 50 competition, sponsored by
Deloitte & Touche LLP.
COMPANY INFORMATION:
Market Technologies Corporation
E-mail address: [email protected]
Website address: www.ProfitTaker.com
Phone: 800-732-5407 or 813-973-0496
Fax: 813-973-2700
25941 Apple Blossom Lane
Wesley Chapel, Florida 33544
Free 2 Week Trial Offer for
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Trend Forecasting With Technical Analysis 119
This book, along
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Market techniques that worked in the last century won’t work in the cur-
rent one. Now, Louis Mendelsohn’s groundbreaking book takes technical
analysis to the next level —giving today’s traders all the tools needed to
make more winning trades —more often.
Mendelsohn presents a comprehensive approach—combining
technical and intermarket analysis into one powerful framework for
accurately forecasting trends.
You’ll also discover . . .
• Precise trading strategies that can be used by both
day traders and position traders
• The limitations of traditional technical analysis methods
• How to use moving averages as a leading—not lagging—indicator
by the application of neural networks to intermarket analysis
PLUS —an introduction to VantagePoint Software, and its amazing fore-
casting capabilities. This powerful software makes Mendelsohn’s “new
economy”trading methods
work simply—and effectively.
“
Since I was the one who first described inter-
market principles 10 years ago, I feel indebted to
Mendelsohn for proving that those ideas do, in
fact, work and can be profitably applied to the
financial markets.
”
— JOHN MURPHY, President, MurphyMorris.com
$19.95 US
Marketplace Books
P.O. BOX 2466
Ellicott City MD 21041
doc_580077252.pdf