Description
Dimensional Fund Advisors (DFA) is an investment management firm that prides on basing its investment strategies on sound academic research.
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Dimensional Fund Advisors, 2002
Dimensional Fund Advisors (DFA) is an investment management firm that prides on basing its investment strategies on sound academic research. Many of the best known finance research papers of the past two decades (especially those by Eugene Fama and Kenneth French, who work closely with DFA) have led to DFA investment strategies. DFA began as a small-stock fund, attempting to take advantage of the "size affect" (excess performance of small stocks) that had been discovered by a number of academic researchers. Later, DFA added "value" strategies to its mix of offerings. After academic research documented superior performance by value stocks in a multitude of countries, DFA began to create a variety of international value-stock and small-stock investment funds. The company was highly successful, despite missing out on the great 1990s growth-stock boom. DFA's assets grew under management from $8 billion to $40 billion between 1991 and 2002. With value stocks having performed well in the first 2 years of the new decade, DFA is experiencing continued growth of its investor base and is now seeking new areas in which it can add value for investors while continuing to claim to have no special "stock-picking" ability. In order to analyse the case, we proceed by answering the following questions. These will in-turn leads to a greater understanding about DFA and its strategies and also pave the way for ideas on its future approach. 1. What is DFA’s business strategy? What do you think of the firm? Are the DFA people really believers in efficient markets? DFA started by investing in stocks whose market capitalization was below a cutoff set by 20th percentile of all NYSE stocks. For the “small-stock” fund the stocks selected had market capitalization between ninth and tenth NYSE deciles. Along with it DFA also introduced small company portfolio consisting of stocks in 6-10 NYSE deciles. To select stocks they followed the paper published by Fama and French, which stated that high BE/ME are “value” stocks whereas low BE/ME are “growth” stocks. They would consistently pick “value” stocks for their portfolio.
DFA Case Analysis – Group 11
Page 2
They had two portfolios “SMB”, small minus big, in which they held small stocks but shorted big stocks. The second was “HML”, high-minus-low BE/ME, in which they held value stocks for long and shorted growth stocks. The Tax-Managed DFA International Value Portfolio is a no-load mutual fund designed to achieve long-term capital appreciation. The Portfolio pursues its objective by investing in the stocks of large non-US companies which the Advisor believes to be value stocks at the time of purchase. Securities are considered value stocks primarily because a company's shares have a high book value in relation to their market value (BtM). This BtM sort excludes firms with negative or zero book values. In assessing value, additional factors such as price to cash flow or price to earnings ratios may be considered, as well as economic conditions and developments in the issuer's industry. The criteria for assessing value are subject to change from time to time. The Portfolio seeks to minimize the impact of federal taxes on returns by deferring the realization of net capital gains and attempting to minimize the receipt of dividend income in order to minimize the taxable distributions to investors. The Portfolio currently invests in companies in Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, and United Kingdom. All these strategies will work only if the markets are efficient. Thus DFA firmly believed that markets were efficient. At the same time they relied heavily on sound academic research. They used to have association with academicians to get access to latest findings. This enabled them to alter their strategies before the other players in the market knew about it. 2. Do the Fama-French findings make sense? Should we expect small stocks to outperform large stocks in the future? Value stocks to outperform growth stocks? Gene Fama and Ken French created an asset pricing model in the mid 1990s that “considers the fact that two particular types of stocks outperform markets on a regular basis: value and small-capsi.” Basically, Fama and French noticed that there were two classes of stocks that continued to out-perform the market as a whole. As mentioned in the quote above, these were
DFA Case Analysis – Group 11
Page 3
? ?
Small caps and Value stocks
The Fama/French results have important implications. Large cap growth stocks constitute large parts of traditional "market-like portfolios" based on indexes such as the S&P 500 and the Russell 3000. “Domestic equity portfolios with greater commitments to small cap stocks and value stocks offer higher average returns than conventional market-like portfolios.”ii This quote clearly re-enforces the purpose for why the model was created. SMB and HML stand for "small minus big" and "high minus low". They measure the historic excess returns of small caps and "value" stocks respectively. Fama and French also examined a market factor. A market factor is needed to distinguish stocks from fixed income securities and is important in explaining the variation of stock returns through time. But, among stocks in a given time period, differences in their sensitivities to the market factor are unrelated to differences in their average returns, so the market factor was established as not a dimension of stock returns. In simplified terms, the model punishes these two types of stocks. It’s interesting to note that Fama and French are advocates of the Efficient Market Hypothesis. Fama and French see high returns as a reward for taking on high risk. In particular, if returns increase with book/price, then stocks with a high book/price ratio must be more risky than average - the opposite of what a traditional business analyst would advise. One of the more interesting implications is that the r-squared value has been improved in the model. Like the CAPM, the Fama and French model is used to explain the performance of portfolios via linear regression; only now the two extra factors give you two additional axes, so instead of a simple line, the regression is a flat surface area. It is difficult to accurately visualise this regression however it is still possible to solve for its coefficients in a spreadsheet. The typical result is a better fit to the data points than you get with the CAPM, with an r-squared in the mid-ninety percent range instead of the mid eighties. Nevertheless, there are two outstanding issues with the FF model. First, the model is empirically driven. It is not a clear whether HML and SMB are related to fundamental
DFA Case Analysis – Group 11 Page 4
economic risk. Fama and French never stated any methodology behind their findings. They do not inform why their model holds and why small cap and value stocks generate on average, higher returns than market stocks. This has been noted as one of the major flaws in the model Second, as Cochrane (1996 and 2001) argues, asset pricing models that use portfolio returns as factors may be successful in describing asset returns, but they will never be able to explain them. The reason is that these models leave unanswered the question of what explains the return-based factors. There are two separate messages to be analysed from the studies of the Three Factor model. Firstly, the three factors together account for practically all of a portfolio's behaviour. Second, history indicates that small value happens to deliver higher returns and higher volatility than the stock market as a whole. Assuming the trend holds, then that's the practical message for investors. For a medium to long term investor, the Fama/French model seems to be quite attractive. Below is empirical evidence from the dimensional website. The graph below shows arithmetic averages and standard deviations of the 1927-2001 annual returns of four asset class portfolios. Size (large and small) and value (low and high) to form these asset class portfolios group stocks As a comparison, statistics also are shown for two market indexes: the S&P 500 (a composite of large cap stocks) and the CRSP 6-10 (a composite of small cap stocks).
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It should be noted that in comparing large cap value to small cap value and comparing large cap growth to small cap growth, small cap stocks had higher average returns than large cap stocks. Additionally, comparing small cap growth to small cap value, value stocks had higher average returns than growth stocks. The higher average returns of small cap and value stocks represent rewards for bearing risk. Hence the obvious benefits for medium-long term investors. The classification of size and value factors by Fama and French and the abnormal returns on them have important implications for portfolios. Structured portfolios can be designed that provide targeted sensitivities to the size and value factors. International and emerging market equity returns also portray the size and value effects. “Structured portfolios only make sense for investors with long time horizons and sufficient tolerance for increased risk.” Empirical Evidence The following data applies to the period of January 1980 through to October 2002 and portrays the proportionate performance of the large company, small company and value indexes. These are the gross performances of the ASX200 index and the MSCI World Index, both representing large companies. The other indexes are actually the small and value index funds available from Dimensional Fund.
It can be seen from the graphs that over the period, the Australian small cap stocks receive
DFA Case Analysis – Group 11 Page 6
lower returns than the index ASX200, however the Aus value receives a great deal more, both without much differing in the Standard Deviation. Similarly, the small caps and value stocks for the MSCI indexes both receive higher returns, noting also smaller standard deviations. The evidence in the study again supports the Fama and French model. Below is further evidence that suggests that medium-long term investors would benefit from investing into the specific stocks. The table below outlines the estimates for the Fama/French model using differing data groups. The data was taken monthly from 19922001.
? S&P 500 Index t-statistics Russell 3000 Index t-statistics DFA Small Cap Portfolio t-statistics DFA Micro Cap Portfolio t-statistics DFA Large Value Portfolio t-statistics DFA Small Value Portfolio t-statistics 0.03 0.75 -0.01 -0.32 0.05 0.42 0.28 1.74 0.00 0.01 0.24 1.88
?3 1.00 0.10 1.00
bs
bv
Adjusted R-squared 0.989
-0.17 0.05 -15.20 5.22 -0.05 0.04
0.997
-0.18 -8.09 7.75 0.88 0.90 0.10 0.953
-4.17 28.92 3.36 0.81 1.09 0.04 0.918
-4.50 23.74 0.86 1.08 1.83 0.84 0.04 0.73 0.81 0.61 13.56 0.39 0.911 0.836
-4.80 22.21 11.65
DFA Case Analysis – Group 11
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t-statistics are in italics. For the market sensitivity coefficient, the null hypothesis is b=1. For the other coefficients, the null hypothesis is that each equals zero. Underlined type indicates statistical significance at the .01 level (2-tailed). Sensitivity to the market factor ?3: The estimates of ?3b are close to 1.00 for the S&P 500, the Russell 3000 and the DFA Large Cap Value Portfolio. The DFA Small Cap Portfolio, Micro Cap Portfolio and Small Value Portfolio are less sensitive to overall market movements. Relative to the market, these small-cap stock portfolios behave like a portfolio composed roughly of 85 percent stocks and 15 percent bonds. Sensitivity to the size factor bs: The S&P 500 and Russell 3000 are predominantly large-cap stock indexes, and their excess returns are negatively related to the size factor. The DFA Large Cap Value Portfolio's sensitivity to the size factor is effectively zero. The three DFA small-cap portfolios have strong, positive sensitivities to the size factor. Sensitivity to the value factor bv: The DFA Micro Cap Portfolio's sensitivity to the value factor is effectively zero. The estimated value sensitivities of the other five portfolios are positive, and the value sensitivities of the DFA Large Cap Value and Small Cap Value Portfolios are much greater than the others. Assumptions Although the assumptions were outlined in the section on Fama and French, for the purpose of our choice to accept it as an investment strategy will require a brief re-run over the ideology behind it. The Fama/French Three-Factor Model was structured initially on a survey of stocks. Using regression techniques, they established an orderly model that managed to define market returns quite well. Their main assumptions/hypothesis was that an investor can influence his or her return by varying three factors: 1. How much stock market exposure to accept. 2. The size ranking of the companies bought. 3. The book to market ratio.
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Although Fama and French discovered a model that seemed functional, they are still struggling with identifying the hidden risks that explain these anomalies. Generally these assumptions of the model are quite restrictive as they include stocks specific to the three factors. The model is based on empirical research and therefore does not hold a great deal of significance with relevance to economists and economic reasoning. 3. Why has DFA’s small stock fund performed so well? The small stocks are bought based only their intrinsic value. Along with it they just have quarterly profits to bag their stance. In case of value stocks, their price are already high since majority of players on the stock market have already bought this stocks. Thus, it won’t be possible to gain high returns on the value stocks since the amount of money spent on buying these stocks will be high whereas for small stocks the amount of money spent will be low. Also, in case of DFA’s they bought stocks in bulks from brokers at a discount rate. 4. Is DFA’s tax-managed fund family likely to be successful? Tax-managed funds were a good innovation for DFA, as it allowed the fund to access additional capital from high-net-worth individuals, who are more patient than retail investors and more probably would not withdraw their money in a short period of time (herding). From other hand, tax-managed funds are more risky as they put more weight on dividend free stocks, reducing diversification benefits. Providing clients with better aftertax returns, DFA is increasing the risk of tax-managed portfolios. So, the fee structure should reflect this trade-off. This is why fees for a DFA should be always higher than on passive mutual fund, which works on liquid market.
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5. What should be the firm’s strategy going forward? DFA Philosophy
The firm has been following the strategy of buying and holding value stocks of small companies. DFA assumes that markets do work and that through proper research in financial science, it can capture specific dimensions of risk and try and minimize it, if it cannot completely remove it. It minimizes transactions cost as much as possible and enhances returns to its investors by designing and trading an efficient portfolio, which it creates based on the book-to-market ratio of companies. But recently, many people have concluded that the book-to-market ratio no longer has a place in investment analysis. In particular, strategies that use the book-to-market ratio to identify value stocks have come under attack. We’ll now talk about the company’s strategy of using Book-to-Market ratio and whether it is sound or not Book-to-Market Ratio Issue During the past decade, technology has emerged as a dominant force in the US and world economies. The value that has been created by technological innovations is enormous. One of the criticisms of current accounting procedures is the fact that much of this technologically based economic value is created by investments that are not found anywhere on a firm's balance sheet. Consequently, book value of common equity may be a downward-biased estimate of net asset value for some firms, especially in recent years. According to this view, the new economy has made book value (as currently calculated)
DFA Case Analysis – Group 11 Page 10
obsolete. Extending this argument, some have argued that variables based on book value are also obsolete. As a result, ranking firms on BtM is viewed by some as a waste of time. Even if book value does not accurately measure net assets for some firms, it does not necessarily follow that ranking firms on BtM is useless. Suppose a particular industry has tremendous growth prospects, and the firms in this industry all have BtM ratios around 0.1. They all appear in the bottom decile of the current BtM ranking. Now suppose that accounting procedures are retroactively changed, so that R&D and similar expenditures are capitalized, instead of being expensed. The result is an increase in book value for nearly all firms and an especially large increase for the firms in this industry. Suppose the accounting change doubles their book values, so that their BtM ratios are now around 0.2. Although their BtM ratios increased more than those of most other firms, they are still in the bottom 25% of the BtM ranking, and nobody is in danger of adding them to a portfolio of value stocks. As long as value stocks (i.e., firms that are deemed by investors to be in distress and have poor growth prospects) have higher BtM ratios than other stocks, ranking on BtM will continue to be a valid way of identifying these stocks. The best measure to judge whether ranking on BtM still allows us to identify value stocks is dispersion in returns. Value stocks have had higher average returns than growth stocks for the past several decades, although there have been periods when this was not true (1999, for example). If a variable like BtM is still valid for distinguishing value stocks from growth stocks, we should see return differences for stocks at opposite ends of the BtM ranking. Proponents of the new economy criticisms of book value would claim that the strong crosssectional relation between BtM and returns should have weakened in recent years as the nature of the US economy has changed. There is no evidence of BtM becoming irrelevant for identifying value stocks. Compared to popular alternatives, BtM is at least as good at producing dispersion in average returns. This ability has not declined in recent years. The changes in the composition of the US and world economies during the past several years have not eliminated the strong crosssectional relation between BtM and realized returns. There is one advantage of BtM relative to its peers that should be mentioned. Since book value is a "stock" variable, while earnings, cash flow and sales are "flow" variables, there is a tendency for BtM rankings to be somewhat more stable over time than the rankings based on the other three variables. This reduces portfolio turnover for strategies that are
DFA Case Analysis – Group 11 Page 11
based on BtM rankings. So, in addition to providing at least as much return dispersion as its competitors, BtM may also reduce the number of transactions that are triggered by stocks moving in and out of the portfolio's buy range. This can be especially important for taxable investors. Therefore, we conclude that DFA should proceed with its strategy of using Bookto Market Ratio. DFA Future Strategies Small Cap Strategies Dimensional Fund Advisor has been a pioneer in small stock research since 1981. Research documents that, over the long term, small companies provide higher expected returns than larger companies. DFA's objective is to deliver a small cap performance premium and provide worldwide diversification. DFA defines small companies as those whose market capitalization comprises the smallest 10% of the total market universe or that are smaller than the 1,000th largest company in the universe, whichever results in a higher market capitalization break. It should have different portfolios, for both micro companies and small companies. DFA should focus on creating portfolios that buys securities of US companies whose size falls within the smallest 4% of the total market universe. This will constitute the companies that come under the Micro Companies Portfolio. DFA’s Small Companies Portfolio should buy securities of those US companies whose size falls within the smallest 8% of the total market universe. The portfolio's hold range should extend only through the bottom 10% of companies or below the 1,000th largest company in the universe, whichever is higher. A "buffer" range can be created to allow the portfolio strategies to hold securities that grow out of the buy range, in order to minimize transaction costs and keep portfolio turnover low. Additional screening criteria should be employed to eliminate securities that do not display the common qualities of the asset class or that lack sufficient liquidity for cost-effective trading.
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Value Strategies DFA's value strategies are based on the Fama/French research and are designed to capture the return premiums associated with high book-to-market (BtM) ratios. Their value portfolios are constructed by first ranking the total market universe by market cap and identifying those companies that fall within the defined size range. This universe is then ranked by BtM ratio. Tax-Managed Strategies DFA should get more involved in creating tax-efficient mutual funds to target market segments that require higher expected returns but are otherwise costly or unsuitable for taxable investors. The tax-managed strategies should deliver the same strong, consistent exposure to their asset classes that DFA is known for, but with a special emphasis on capturing after-tax returns. DFA's Tax-Managed strategies open new opportunities for taxable investors. Asset classes that were previously suited to non-taxable investors now make sense for everyone. The Fama/French research found a way to offset gains and minimize dividends without sacrificing strong diversified exposure to specific asset classes or across asset classes. As a result, the full benefits of engineered approaches like DFA’s value strategies are no longer reserved for non-taxable corporate plans. Passive Management Active management is always a zero sum game, before fees, expenses, and trading costs, regardless of market conditions. If there are active winners, they win at the expense of active losers. And active management is always a negative sum game after costs. This is an algebraic condition, not a hypothesis. This is called as equilibrium accounting. Moreover, the research by Fama and French on individual mutual funds says that it's impossible to identify true winners on a reliable basis, even if one ignores the costs that active funds impose on investors. Funds that seem to be winners, based on past returns, were probably lucky rather than smart. After costs, that is in terms of returns to investors, there is no game to play; there is no evidence of managers with enough information to cover costs, other than on a purely chance basis. And there is no evidence that this depends on market conditions.
DFA Case Analysis – Group 11 Page 13
In short, passive management and passive investing always make sense. Therefore, DFA must continue with its passive management strategy.
References
http://www.dfaus.com
http://finance.commerce.ubc.ca/~carlsonm/comm472/Assignment2.doc http://www.dimensional.com/famafrench/ “Investments”- book by Bodie, Kane, Marcus, and Mohanty
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i ii
Small Caps- see http://www.investopedia.com/terms/s/small-cap.asp http://library.dimensional.com.au/articles/dimensions_stock_returns_2002/
DFA Case Analysis – Group 11
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doc_558539344.pdf
Dimensional Fund Advisors (DFA) is an investment management firm that prides on basing its investment strategies on sound academic research.
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Dimensional Fund Advisors, 2002
Dimensional Fund Advisors (DFA) is an investment management firm that prides on basing its investment strategies on sound academic research. Many of the best known finance research papers of the past two decades (especially those by Eugene Fama and Kenneth French, who work closely with DFA) have led to DFA investment strategies. DFA began as a small-stock fund, attempting to take advantage of the "size affect" (excess performance of small stocks) that had been discovered by a number of academic researchers. Later, DFA added "value" strategies to its mix of offerings. After academic research documented superior performance by value stocks in a multitude of countries, DFA began to create a variety of international value-stock and small-stock investment funds. The company was highly successful, despite missing out on the great 1990s growth-stock boom. DFA's assets grew under management from $8 billion to $40 billion between 1991 and 2002. With value stocks having performed well in the first 2 years of the new decade, DFA is experiencing continued growth of its investor base and is now seeking new areas in which it can add value for investors while continuing to claim to have no special "stock-picking" ability. In order to analyse the case, we proceed by answering the following questions. These will in-turn leads to a greater understanding about DFA and its strategies and also pave the way for ideas on its future approach. 1. What is DFA’s business strategy? What do you think of the firm? Are the DFA people really believers in efficient markets? DFA started by investing in stocks whose market capitalization was below a cutoff set by 20th percentile of all NYSE stocks. For the “small-stock” fund the stocks selected had market capitalization between ninth and tenth NYSE deciles. Along with it DFA also introduced small company portfolio consisting of stocks in 6-10 NYSE deciles. To select stocks they followed the paper published by Fama and French, which stated that high BE/ME are “value” stocks whereas low BE/ME are “growth” stocks. They would consistently pick “value” stocks for their portfolio.
DFA Case Analysis – Group 11
Page 2
They had two portfolios “SMB”, small minus big, in which they held small stocks but shorted big stocks. The second was “HML”, high-minus-low BE/ME, in which they held value stocks for long and shorted growth stocks. The Tax-Managed DFA International Value Portfolio is a no-load mutual fund designed to achieve long-term capital appreciation. The Portfolio pursues its objective by investing in the stocks of large non-US companies which the Advisor believes to be value stocks at the time of purchase. Securities are considered value stocks primarily because a company's shares have a high book value in relation to their market value (BtM). This BtM sort excludes firms with negative or zero book values. In assessing value, additional factors such as price to cash flow or price to earnings ratios may be considered, as well as economic conditions and developments in the issuer's industry. The criteria for assessing value are subject to change from time to time. The Portfolio seeks to minimize the impact of federal taxes on returns by deferring the realization of net capital gains and attempting to minimize the receipt of dividend income in order to minimize the taxable distributions to investors. The Portfolio currently invests in companies in Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, and United Kingdom. All these strategies will work only if the markets are efficient. Thus DFA firmly believed that markets were efficient. At the same time they relied heavily on sound academic research. They used to have association with academicians to get access to latest findings. This enabled them to alter their strategies before the other players in the market knew about it. 2. Do the Fama-French findings make sense? Should we expect small stocks to outperform large stocks in the future? Value stocks to outperform growth stocks? Gene Fama and Ken French created an asset pricing model in the mid 1990s that “considers the fact that two particular types of stocks outperform markets on a regular basis: value and small-capsi.” Basically, Fama and French noticed that there were two classes of stocks that continued to out-perform the market as a whole. As mentioned in the quote above, these were
DFA Case Analysis – Group 11
Page 3
? ?
Small caps and Value stocks
The Fama/French results have important implications. Large cap growth stocks constitute large parts of traditional "market-like portfolios" based on indexes such as the S&P 500 and the Russell 3000. “Domestic equity portfolios with greater commitments to small cap stocks and value stocks offer higher average returns than conventional market-like portfolios.”ii This quote clearly re-enforces the purpose for why the model was created. SMB and HML stand for "small minus big" and "high minus low". They measure the historic excess returns of small caps and "value" stocks respectively. Fama and French also examined a market factor. A market factor is needed to distinguish stocks from fixed income securities and is important in explaining the variation of stock returns through time. But, among stocks in a given time period, differences in their sensitivities to the market factor are unrelated to differences in their average returns, so the market factor was established as not a dimension of stock returns. In simplified terms, the model punishes these two types of stocks. It’s interesting to note that Fama and French are advocates of the Efficient Market Hypothesis. Fama and French see high returns as a reward for taking on high risk. In particular, if returns increase with book/price, then stocks with a high book/price ratio must be more risky than average - the opposite of what a traditional business analyst would advise. One of the more interesting implications is that the r-squared value has been improved in the model. Like the CAPM, the Fama and French model is used to explain the performance of portfolios via linear regression; only now the two extra factors give you two additional axes, so instead of a simple line, the regression is a flat surface area. It is difficult to accurately visualise this regression however it is still possible to solve for its coefficients in a spreadsheet. The typical result is a better fit to the data points than you get with the CAPM, with an r-squared in the mid-ninety percent range instead of the mid eighties. Nevertheless, there are two outstanding issues with the FF model. First, the model is empirically driven. It is not a clear whether HML and SMB are related to fundamental
DFA Case Analysis – Group 11 Page 4
economic risk. Fama and French never stated any methodology behind their findings. They do not inform why their model holds and why small cap and value stocks generate on average, higher returns than market stocks. This has been noted as one of the major flaws in the model Second, as Cochrane (1996 and 2001) argues, asset pricing models that use portfolio returns as factors may be successful in describing asset returns, but they will never be able to explain them. The reason is that these models leave unanswered the question of what explains the return-based factors. There are two separate messages to be analysed from the studies of the Three Factor model. Firstly, the three factors together account for practically all of a portfolio's behaviour. Second, history indicates that small value happens to deliver higher returns and higher volatility than the stock market as a whole. Assuming the trend holds, then that's the practical message for investors. For a medium to long term investor, the Fama/French model seems to be quite attractive. Below is empirical evidence from the dimensional website. The graph below shows arithmetic averages and standard deviations of the 1927-2001 annual returns of four asset class portfolios. Size (large and small) and value (low and high) to form these asset class portfolios group stocks As a comparison, statistics also are shown for two market indexes: the S&P 500 (a composite of large cap stocks) and the CRSP 6-10 (a composite of small cap stocks).
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Page 5
It should be noted that in comparing large cap value to small cap value and comparing large cap growth to small cap growth, small cap stocks had higher average returns than large cap stocks. Additionally, comparing small cap growth to small cap value, value stocks had higher average returns than growth stocks. The higher average returns of small cap and value stocks represent rewards for bearing risk. Hence the obvious benefits for medium-long term investors. The classification of size and value factors by Fama and French and the abnormal returns on them have important implications for portfolios. Structured portfolios can be designed that provide targeted sensitivities to the size and value factors. International and emerging market equity returns also portray the size and value effects. “Structured portfolios only make sense for investors with long time horizons and sufficient tolerance for increased risk.” Empirical Evidence The following data applies to the period of January 1980 through to October 2002 and portrays the proportionate performance of the large company, small company and value indexes. These are the gross performances of the ASX200 index and the MSCI World Index, both representing large companies. The other indexes are actually the small and value index funds available from Dimensional Fund.
It can be seen from the graphs that over the period, the Australian small cap stocks receive
DFA Case Analysis – Group 11 Page 6
lower returns than the index ASX200, however the Aus value receives a great deal more, both without much differing in the Standard Deviation. Similarly, the small caps and value stocks for the MSCI indexes both receive higher returns, noting also smaller standard deviations. The evidence in the study again supports the Fama and French model. Below is further evidence that suggests that medium-long term investors would benefit from investing into the specific stocks. The table below outlines the estimates for the Fama/French model using differing data groups. The data was taken monthly from 19922001.
? S&P 500 Index t-statistics Russell 3000 Index t-statistics DFA Small Cap Portfolio t-statistics DFA Micro Cap Portfolio t-statistics DFA Large Value Portfolio t-statistics DFA Small Value Portfolio t-statistics 0.03 0.75 -0.01 -0.32 0.05 0.42 0.28 1.74 0.00 0.01 0.24 1.88
?3 1.00 0.10 1.00
bs
bv
Adjusted R-squared 0.989
-0.17 0.05 -15.20 5.22 -0.05 0.04
0.997
-0.18 -8.09 7.75 0.88 0.90 0.10 0.953
-4.17 28.92 3.36 0.81 1.09 0.04 0.918
-4.50 23.74 0.86 1.08 1.83 0.84 0.04 0.73 0.81 0.61 13.56 0.39 0.911 0.836
-4.80 22.21 11.65
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t-statistics are in italics. For the market sensitivity coefficient, the null hypothesis is b=1. For the other coefficients, the null hypothesis is that each equals zero. Underlined type indicates statistical significance at the .01 level (2-tailed). Sensitivity to the market factor ?3: The estimates of ?3b are close to 1.00 for the S&P 500, the Russell 3000 and the DFA Large Cap Value Portfolio. The DFA Small Cap Portfolio, Micro Cap Portfolio and Small Value Portfolio are less sensitive to overall market movements. Relative to the market, these small-cap stock portfolios behave like a portfolio composed roughly of 85 percent stocks and 15 percent bonds. Sensitivity to the size factor bs: The S&P 500 and Russell 3000 are predominantly large-cap stock indexes, and their excess returns are negatively related to the size factor. The DFA Large Cap Value Portfolio's sensitivity to the size factor is effectively zero. The three DFA small-cap portfolios have strong, positive sensitivities to the size factor. Sensitivity to the value factor bv: The DFA Micro Cap Portfolio's sensitivity to the value factor is effectively zero. The estimated value sensitivities of the other five portfolios are positive, and the value sensitivities of the DFA Large Cap Value and Small Cap Value Portfolios are much greater than the others. Assumptions Although the assumptions were outlined in the section on Fama and French, for the purpose of our choice to accept it as an investment strategy will require a brief re-run over the ideology behind it. The Fama/French Three-Factor Model was structured initially on a survey of stocks. Using regression techniques, they established an orderly model that managed to define market returns quite well. Their main assumptions/hypothesis was that an investor can influence his or her return by varying three factors: 1. How much stock market exposure to accept. 2. The size ranking of the companies bought. 3. The book to market ratio.
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Although Fama and French discovered a model that seemed functional, they are still struggling with identifying the hidden risks that explain these anomalies. Generally these assumptions of the model are quite restrictive as they include stocks specific to the three factors. The model is based on empirical research and therefore does not hold a great deal of significance with relevance to economists and economic reasoning. 3. Why has DFA’s small stock fund performed so well? The small stocks are bought based only their intrinsic value. Along with it they just have quarterly profits to bag their stance. In case of value stocks, their price are already high since majority of players on the stock market have already bought this stocks. Thus, it won’t be possible to gain high returns on the value stocks since the amount of money spent on buying these stocks will be high whereas for small stocks the amount of money spent will be low. Also, in case of DFA’s they bought stocks in bulks from brokers at a discount rate. 4. Is DFA’s tax-managed fund family likely to be successful? Tax-managed funds were a good innovation for DFA, as it allowed the fund to access additional capital from high-net-worth individuals, who are more patient than retail investors and more probably would not withdraw their money in a short period of time (herding). From other hand, tax-managed funds are more risky as they put more weight on dividend free stocks, reducing diversification benefits. Providing clients with better aftertax returns, DFA is increasing the risk of tax-managed portfolios. So, the fee structure should reflect this trade-off. This is why fees for a DFA should be always higher than on passive mutual fund, which works on liquid market.
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5. What should be the firm’s strategy going forward? DFA Philosophy
The firm has been following the strategy of buying and holding value stocks of small companies. DFA assumes that markets do work and that through proper research in financial science, it can capture specific dimensions of risk and try and minimize it, if it cannot completely remove it. It minimizes transactions cost as much as possible and enhances returns to its investors by designing and trading an efficient portfolio, which it creates based on the book-to-market ratio of companies. But recently, many people have concluded that the book-to-market ratio no longer has a place in investment analysis. In particular, strategies that use the book-to-market ratio to identify value stocks have come under attack. We’ll now talk about the company’s strategy of using Book-to-Market ratio and whether it is sound or not Book-to-Market Ratio Issue During the past decade, technology has emerged as a dominant force in the US and world economies. The value that has been created by technological innovations is enormous. One of the criticisms of current accounting procedures is the fact that much of this technologically based economic value is created by investments that are not found anywhere on a firm's balance sheet. Consequently, book value of common equity may be a downward-biased estimate of net asset value for some firms, especially in recent years. According to this view, the new economy has made book value (as currently calculated)
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obsolete. Extending this argument, some have argued that variables based on book value are also obsolete. As a result, ranking firms on BtM is viewed by some as a waste of time. Even if book value does not accurately measure net assets for some firms, it does not necessarily follow that ranking firms on BtM is useless. Suppose a particular industry has tremendous growth prospects, and the firms in this industry all have BtM ratios around 0.1. They all appear in the bottom decile of the current BtM ranking. Now suppose that accounting procedures are retroactively changed, so that R&D and similar expenditures are capitalized, instead of being expensed. The result is an increase in book value for nearly all firms and an especially large increase for the firms in this industry. Suppose the accounting change doubles their book values, so that their BtM ratios are now around 0.2. Although their BtM ratios increased more than those of most other firms, they are still in the bottom 25% of the BtM ranking, and nobody is in danger of adding them to a portfolio of value stocks. As long as value stocks (i.e., firms that are deemed by investors to be in distress and have poor growth prospects) have higher BtM ratios than other stocks, ranking on BtM will continue to be a valid way of identifying these stocks. The best measure to judge whether ranking on BtM still allows us to identify value stocks is dispersion in returns. Value stocks have had higher average returns than growth stocks for the past several decades, although there have been periods when this was not true (1999, for example). If a variable like BtM is still valid for distinguishing value stocks from growth stocks, we should see return differences for stocks at opposite ends of the BtM ranking. Proponents of the new economy criticisms of book value would claim that the strong crosssectional relation between BtM and returns should have weakened in recent years as the nature of the US economy has changed. There is no evidence of BtM becoming irrelevant for identifying value stocks. Compared to popular alternatives, BtM is at least as good at producing dispersion in average returns. This ability has not declined in recent years. The changes in the composition of the US and world economies during the past several years have not eliminated the strong crosssectional relation between BtM and realized returns. There is one advantage of BtM relative to its peers that should be mentioned. Since book value is a "stock" variable, while earnings, cash flow and sales are "flow" variables, there is a tendency for BtM rankings to be somewhat more stable over time than the rankings based on the other three variables. This reduces portfolio turnover for strategies that are
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based on BtM rankings. So, in addition to providing at least as much return dispersion as its competitors, BtM may also reduce the number of transactions that are triggered by stocks moving in and out of the portfolio's buy range. This can be especially important for taxable investors. Therefore, we conclude that DFA should proceed with its strategy of using Bookto Market Ratio. DFA Future Strategies Small Cap Strategies Dimensional Fund Advisor has been a pioneer in small stock research since 1981. Research documents that, over the long term, small companies provide higher expected returns than larger companies. DFA's objective is to deliver a small cap performance premium and provide worldwide diversification. DFA defines small companies as those whose market capitalization comprises the smallest 10% of the total market universe or that are smaller than the 1,000th largest company in the universe, whichever results in a higher market capitalization break. It should have different portfolios, for both micro companies and small companies. DFA should focus on creating portfolios that buys securities of US companies whose size falls within the smallest 4% of the total market universe. This will constitute the companies that come under the Micro Companies Portfolio. DFA’s Small Companies Portfolio should buy securities of those US companies whose size falls within the smallest 8% of the total market universe. The portfolio's hold range should extend only through the bottom 10% of companies or below the 1,000th largest company in the universe, whichever is higher. A "buffer" range can be created to allow the portfolio strategies to hold securities that grow out of the buy range, in order to minimize transaction costs and keep portfolio turnover low. Additional screening criteria should be employed to eliminate securities that do not display the common qualities of the asset class or that lack sufficient liquidity for cost-effective trading.
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Value Strategies DFA's value strategies are based on the Fama/French research and are designed to capture the return premiums associated with high book-to-market (BtM) ratios. Their value portfolios are constructed by first ranking the total market universe by market cap and identifying those companies that fall within the defined size range. This universe is then ranked by BtM ratio. Tax-Managed Strategies DFA should get more involved in creating tax-efficient mutual funds to target market segments that require higher expected returns but are otherwise costly or unsuitable for taxable investors. The tax-managed strategies should deliver the same strong, consistent exposure to their asset classes that DFA is known for, but with a special emphasis on capturing after-tax returns. DFA's Tax-Managed strategies open new opportunities for taxable investors. Asset classes that were previously suited to non-taxable investors now make sense for everyone. The Fama/French research found a way to offset gains and minimize dividends without sacrificing strong diversified exposure to specific asset classes or across asset classes. As a result, the full benefits of engineered approaches like DFA’s value strategies are no longer reserved for non-taxable corporate plans. Passive Management Active management is always a zero sum game, before fees, expenses, and trading costs, regardless of market conditions. If there are active winners, they win at the expense of active losers. And active management is always a negative sum game after costs. This is an algebraic condition, not a hypothesis. This is called as equilibrium accounting. Moreover, the research by Fama and French on individual mutual funds says that it's impossible to identify true winners on a reliable basis, even if one ignores the costs that active funds impose on investors. Funds that seem to be winners, based on past returns, were probably lucky rather than smart. After costs, that is in terms of returns to investors, there is no game to play; there is no evidence of managers with enough information to cover costs, other than on a purely chance basis. And there is no evidence that this depends on market conditions.
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In short, passive management and passive investing always make sense. Therefore, DFA must continue with its passive management strategy.
References
http://www.dfaus.com
http://finance.commerce.ubc.ca/~carlsonm/comm472/Assignment2.doc http://www.dimensional.com/famafrench/ “Investments”- book by Bodie, Kane, Marcus, and Mohanty
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i ii
Small Caps- see http://www.investopedia.com/terms/s/small-cap.asp http://library.dimensional.com.au/articles/dimensions_stock_returns_2002/
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doc_558539344.pdf