Description
Business Intelligence Tools And Micro-data Related To The South African Equities Market
IFC Bulletin No 37 141
Business intelligence tools and micro-data related to
the South African equities market: application and
experience
Zeph Nhleko
1
Abstract
Fully understanding the meaning of equities market statistics has become an
increasingly difficult task in recent years. Following the financial crisis many well-
established relationships and causalities in the market have been weakened
somewhat. This makes the necessity for monetary policy-makers to analyse equities
statistics in a granular manner much more pronounced. The use of business
intelligence tools and micro-data sets for this purpose has never been more
relevant. This note seeks to outline how such tools have been applied to extensive
micro-data sets in the South African equities market environment.
Keywords: micro-data, all-share price index, business intelligence
1
Head, Capital Market and Flow of Funds, Research Department, South African Reserve Bank,
[email protected]. The views expressed are those of the author and do not necessarily
reflect the views of the South African Reserve Bank.
142 IFC Bulletin No 37
1. Introduction
The purpose of this note is to show how business intelligence tools and micro-data
may be combined to provide a view on developments in equity prices. Business
intelligence tools in this context refer to software or applications that can be used in
a central banking environment to analyse, query and report on capital market data.
In particular, I-Net Station by I-Net Bridge (I-Net) and Reuters Eikon by Thompson
Reuters (Reuters) are considered here. I-Net is a South African financial services
company that specialises in providing economic data, financial market data and
corporate market intelligence in South Africa. Reuters provides a synthesis of human
intelligence, industry expertise and innovative technology to deliver insight to,
among others, financial, risk, legal, tax and accounting markets. Micro-data on the
other hand is used here to refer to individual listed company data on South Africa’s
stock exchange, the JSE Limited (JSE). Such data include volumes, values and prices
at company level in the market.
2. Rationale for using equities market micro-data to assess
equity price developments in South Africa
The focus of this note is on equities and, in particular, trying to understand the role
of dual-listed shares on the overall all-share price index (Alsi) of the JSE. The Alsi is a
free-float, market capitalization weighted index that tracks the performance of all
companies listed on the JSE. It is the broadest and representative measure of the
exchange’s performance. There is a view
2
that dual listed shares may reflect
offshore sentiment or developments and the rand exchange rate movements – and
may as such influence the overall share market in South Africa. This view finds
further support from the fact that the weight of dual-listed shares on the Alsi is over
65 per cent. However the concept of dual listing can be confusing at times
3
and
must be carefully interpreted – a couple of points are important in this regard.
Firstly, the extent of dual listing (in percentages) varies across companies and
this may affect the level of impact such shares may have on the domestic market.
Secondly, the standard dual listing status of a company does not take into account
depository receipts, i.e., negotiable financial instruments issued by banks to
represent foreign companies’ publicly listed shares. Although some companies
listed on the JSE do not have secondary listings, they have depository receipt
programs with banks offshore. Typically these banks list the shares on offshore
exchanges to be traded by non-residents. Thirdly, some companies, even though
they are only listed domestically, have foreign ownership in excess of 50 per cent,
which should make them susceptible to offshore sentiment and developments.
Fourthly, the objective for buying certain shares may actually have nothing to do
with investor sentiment or economic factors for that matter, as such shares may be
2
For example, (1) Internal discussions, (2) Uranium One prejudiced by JSE rules,http://www.miningmx.com/..._site_id=83 and (3) Arbitrage opportunities on dual-listed stockshttp://www.moneyweb.co.za/...-duallisted-stocks.
3
E-mail response to questions posed, Mark Randall, Manager – Indices: Post Trade Services, JSE
Limited.
IFC Bulletin No 37 143
bought to be defensive or for growth purposes. Lastly, the proportion of revenue
earned in South Africa will make shares sensitive to a certain degree to domestic
factors.
However one assessment that can be done to check the validity of this view is
to analyse the drivers of each share on the JSE. Another assessment is to compute
separate indices for dual-listed shares (DLSi) and non-dual-listed shares (NDLSi) for
South Africa. Similar to the Alsi, these indices should be weighted indices that
include/exclude the dual-listed companies in order to capture the supposedly
domestic economic and other influences on share prices. Companies whose dual
listing is in Africa need not be excluded from the index as the impact of their share
price movements would be minimal on the JSE. Based on current listing and for
purposes of calculating these indices, “dual-listed” means listed at the JSE and
outside Africa.
There are several ways of compiling indices, but the two most basic formulae
for computing indices are the Paasche and Laspeyres
4
methodologies. The only real
difference between them is that the Paasche index uses the number
of quantities
and the Laspeyres index uses base period (0) quantities. The indices take the
following forms respectively;
I
p
=
?( ?p
t
n
× ?q
t
n
)
?( ?p
t
0
× ?q
t
n
)
and I
I
=
?( ?p
t
n
× ?q
t
0
)
?( ?p
t
0
× ?q
t
0
)
where p is the price level, t
0
is the base period and t
n
is the number of periods
for which the index is computed. Adapting the Laspeyres methodology and in line
with JSE’s index calculation technique, the proposed DLSi and NDLSi can take the
form;
I =
( p
ì
× s
ì
× ¡
ì
)
J
N
ì=1
where N is the number of securities in the index, p
i
is the latest share price, s
i
is
the number of shares issued or traded, f
i
is the investability factor (free float
weighting) and d is the divisor representing all issued shares at the base period. The
divisor changes with the issued shares in order to avoid distorting the index.
3. Business intelligence tools and the compilation of an
alternative all share price index
The process of calculating the separate indices requires micro-data at individual
company level, such as share prices and individual company volumes of shares
traded on a daily basis. I-Net and Reuters allow for collecting these types of data
over time. These tools allow company code names to be identified separately and
4
Etienne Laspeyres, 1871 and Herman Paasche, 1874.
144 IFC Bulletin No 37
used to compile a matrix with share prices, volumes traded, market capitalisation
and similar variables. Individual company code names can also be used to check
and verify company registration/deregistration dates with the JSE – this is important
information for maintaining the index, i.e., the process of adjusting the index divisor.
4. Conclusion
Figure 1 shows that, although fluctuations are more pronounced, the average prices
of non-dual-listed shares increased by 96 per cent from February 2009 to April
2013, much faster than dual-listed share prices at 67 per cent. The overall Alsi
increased by 87 per cent over this period. The differential between the Alsi, DLSi and
NDLSi represent a confluence of domestic and offshore factors that affect domestic
share prices. Therefore the view that dual-listed shares drive the Alsi more than
other factors has no solid basis. Further analysis is required.
Share prices Figure 1
Non-Dual-Listed share index Dual-Listed share index
200
300
400
500
600
700
800
900
1000
2009 2010 2011 2012 2013
I
n
d
e
x
=
2
J
a
n
u
a
r
y
2
0
0
9
Share price growth Share price growth
80
100
120
140
160
180
2009 2010 2011 2012 2013
I
n
d
e
x
=
2
J
a
n
u
a
r
y
2
0
0
9
All-share price index All-share price index
IFC Bulletin No 37 145
References
Capital Market and Flow of Funds, 2012 (March): Cheapness of the South African
equity market – a perspective on PE ratios, Unpublished.
Capital Market and Flow of Funds, 2012 (July): Performance of the All-share Price
Index (Alsi) and some of its drivers, Unpublished.
Capital Market and Flow of Funds, 2012 (August): Is the compensation for holding
shares vs. bonds negative?, Unpublished.
Chance, W.A. 1966. A note on the origins of index numbers, The Review of
Economics and Statistics, 48 (1). February, pp. 108 – 110.
FTSE/JSE. 2004. Guide to calculation methods for the FTSE/JSE Africa index series.
FTSE/JSE. 2004. Guide to calculation methods for the UK series of the FTSE Actuaries
share indices.
FTSE/JSE. 2012. Ground rules for the management of the FTSE/JSE Africa index
series.
I-Net Bridge, 2013.http://www.inet.co.za/#about_us/company_prof.php. Accessed
10 April 2013.
S&P Indices. 2012. Index mathematics methodology
Thompson Reuters, 2013.http://thomsonreuters.com/about/. Accessed 10 April
2011.
doc_980776132.pdf
Business Intelligence Tools And Micro-data Related To The South African Equities Market
IFC Bulletin No 37 141
Business intelligence tools and micro-data related to
the South African equities market: application and
experience
Zeph Nhleko
1
Abstract
Fully understanding the meaning of equities market statistics has become an
increasingly difficult task in recent years. Following the financial crisis many well-
established relationships and causalities in the market have been weakened
somewhat. This makes the necessity for monetary policy-makers to analyse equities
statistics in a granular manner much more pronounced. The use of business
intelligence tools and micro-data sets for this purpose has never been more
relevant. This note seeks to outline how such tools have been applied to extensive
micro-data sets in the South African equities market environment.
Keywords: micro-data, all-share price index, business intelligence
1
Head, Capital Market and Flow of Funds, Research Department, South African Reserve Bank,
[email protected]. The views expressed are those of the author and do not necessarily
reflect the views of the South African Reserve Bank.
142 IFC Bulletin No 37
1. Introduction
The purpose of this note is to show how business intelligence tools and micro-data
may be combined to provide a view on developments in equity prices. Business
intelligence tools in this context refer to software or applications that can be used in
a central banking environment to analyse, query and report on capital market data.
In particular, I-Net Station by I-Net Bridge (I-Net) and Reuters Eikon by Thompson
Reuters (Reuters) are considered here. I-Net is a South African financial services
company that specialises in providing economic data, financial market data and
corporate market intelligence in South Africa. Reuters provides a synthesis of human
intelligence, industry expertise and innovative technology to deliver insight to,
among others, financial, risk, legal, tax and accounting markets. Micro-data on the
other hand is used here to refer to individual listed company data on South Africa’s
stock exchange, the JSE Limited (JSE). Such data include volumes, values and prices
at company level in the market.
2. Rationale for using equities market micro-data to assess
equity price developments in South Africa
The focus of this note is on equities and, in particular, trying to understand the role
of dual-listed shares on the overall all-share price index (Alsi) of the JSE. The Alsi is a
free-float, market capitalization weighted index that tracks the performance of all
companies listed on the JSE. It is the broadest and representative measure of the
exchange’s performance. There is a view
2
that dual listed shares may reflect
offshore sentiment or developments and the rand exchange rate movements – and
may as such influence the overall share market in South Africa. This view finds
further support from the fact that the weight of dual-listed shares on the Alsi is over
65 per cent. However the concept of dual listing can be confusing at times
3
and
must be carefully interpreted – a couple of points are important in this regard.
Firstly, the extent of dual listing (in percentages) varies across companies and
this may affect the level of impact such shares may have on the domestic market.
Secondly, the standard dual listing status of a company does not take into account
depository receipts, i.e., negotiable financial instruments issued by banks to
represent foreign companies’ publicly listed shares. Although some companies
listed on the JSE do not have secondary listings, they have depository receipt
programs with banks offshore. Typically these banks list the shares on offshore
exchanges to be traded by non-residents. Thirdly, some companies, even though
they are only listed domestically, have foreign ownership in excess of 50 per cent,
which should make them susceptible to offshore sentiment and developments.
Fourthly, the objective for buying certain shares may actually have nothing to do
with investor sentiment or economic factors for that matter, as such shares may be
2
For example, (1) Internal discussions, (2) Uranium One prejudiced by JSE rules,http://www.miningmx.com/..._site_id=83 and (3) Arbitrage opportunities on dual-listed stockshttp://www.moneyweb.co.za/...-duallisted-stocks.
3
E-mail response to questions posed, Mark Randall, Manager – Indices: Post Trade Services, JSE
Limited.
IFC Bulletin No 37 143
bought to be defensive or for growth purposes. Lastly, the proportion of revenue
earned in South Africa will make shares sensitive to a certain degree to domestic
factors.
However one assessment that can be done to check the validity of this view is
to analyse the drivers of each share on the JSE. Another assessment is to compute
separate indices for dual-listed shares (DLSi) and non-dual-listed shares (NDLSi) for
South Africa. Similar to the Alsi, these indices should be weighted indices that
include/exclude the dual-listed companies in order to capture the supposedly
domestic economic and other influences on share prices. Companies whose dual
listing is in Africa need not be excluded from the index as the impact of their share
price movements would be minimal on the JSE. Based on current listing and for
purposes of calculating these indices, “dual-listed” means listed at the JSE and
outside Africa.
There are several ways of compiling indices, but the two most basic formulae
for computing indices are the Paasche and Laspeyres
4
methodologies. The only real
difference between them is that the Paasche index uses the number
of quantitiesand the Laspeyres index uses base period (0) quantities. The indices take the
following forms respectively;
I
p
=
?( ?p
t
n
× ?q
t
n
)
?( ?p
t
0
× ?q
t
n
)
and I
I
=
?( ?p
t
n
× ?q
t
0
)
?( ?p
t
0
× ?q
t
0
)
where p is the price level, t
0
is the base period and t
n
is the number of periods
for which the index is computed. Adapting the Laspeyres methodology and in line
with JSE’s index calculation technique, the proposed DLSi and NDLSi can take the
form;
I =
( p
ì
× s
ì
× ¡
ì
)
J
N
ì=1
where N is the number of securities in the index, p
i
is the latest share price, s
i
is
the number of shares issued or traded, f
i
is the investability factor (free float
weighting) and d is the divisor representing all issued shares at the base period. The
divisor changes with the issued shares in order to avoid distorting the index.
3. Business intelligence tools and the compilation of an
alternative all share price index
The process of calculating the separate indices requires micro-data at individual
company level, such as share prices and individual company volumes of shares
traded on a daily basis. I-Net and Reuters allow for collecting these types of data
over time. These tools allow company code names to be identified separately and
4
Etienne Laspeyres, 1871 and Herman Paasche, 1874.
144 IFC Bulletin No 37
used to compile a matrix with share prices, volumes traded, market capitalisation
and similar variables. Individual company code names can also be used to check
and verify company registration/deregistration dates with the JSE – this is important
information for maintaining the index, i.e., the process of adjusting the index divisor.
4. Conclusion
Figure 1 shows that, although fluctuations are more pronounced, the average prices
of non-dual-listed shares increased by 96 per cent from February 2009 to April
2013, much faster than dual-listed share prices at 67 per cent. The overall Alsi
increased by 87 per cent over this period. The differential between the Alsi, DLSi and
NDLSi represent a confluence of domestic and offshore factors that affect domestic
share prices. Therefore the view that dual-listed shares drive the Alsi more than
other factors has no solid basis. Further analysis is required.
Share prices Figure 1
Non-Dual-Listed share index Dual-Listed share index
200
300
400
500
600
700
800
900
1000
2009 2010 2011 2012 2013
I
n
d
e
x
=
2
J
a
n
u
a
r
y
2
0
0
9
Share price growth Share price growth
80
100
120
140
160
180
2009 2010 2011 2012 2013
I
n
d
e
x
=
2
J
a
n
u
a
r
y
2
0
0
9
All-share price index All-share price index
IFC Bulletin No 37 145
References
Capital Market and Flow of Funds, 2012 (March): Cheapness of the South African
equity market – a perspective on PE ratios, Unpublished.
Capital Market and Flow of Funds, 2012 (July): Performance of the All-share Price
Index (Alsi) and some of its drivers, Unpublished.
Capital Market and Flow of Funds, 2012 (August): Is the compensation for holding
shares vs. bonds negative?, Unpublished.
Chance, W.A. 1966. A note on the origins of index numbers, The Review of
Economics and Statistics, 48 (1). February, pp. 108 – 110.
FTSE/JSE. 2004. Guide to calculation methods for the FTSE/JSE Africa index series.
FTSE/JSE. 2004. Guide to calculation methods for the UK series of the FTSE Actuaries
share indices.
FTSE/JSE. 2012. Ground rules for the management of the FTSE/JSE Africa index
series.
I-Net Bridge, 2013.http://www.inet.co.za/#about_us/company_prof.php. Accessed
10 April 2013.
S&P Indices. 2012. Index mathematics methodology
Thompson Reuters, 2013.http://thomsonreuters.com/about/. Accessed 10 April
2011.
doc_980776132.pdf