Do domestic investors really make more money? The trading performance of investor

groups in an emerging market

Abstract

We investigate the trading performance of domestic versus foreign investors using high-frequency data. Our sample involves over 270 million observations from companies listed on the Egyptian stock exchange (EGX) from 2004-2009. The transaction data includes unique trade identifiers allowing us to classify investors into six categories: Domestic, Arab and Non-Arab (foreign) and each into: individual and institutional. We assess trading performance: (1) short term using relative price ratios and (2) long term using both cumulative returns and total profits. We find that in the short term, domestic institutions trade at significantly better prices than other categories for single listed stocks, but only outperform the non-Arab foreign investor category for cross-listed stocks. This trend is reversed in longer term performance, since non-Arab foreign institutional investors show more superior cumulative returns and profits. The domestic individual category is the loser on all accounts despite their domination of the overall size and value of trading on the stock market consistent with prior literature. This sheds light on the importance of expertise over local knowledge in trading performance.

JEL Classification: G10

Keywords: Foreign investors; domestic investors, Information Asymmetry; Trading Performance; Ownership

1. Introduction

The question of whether foreign or domestic investors perform better in national stock markets is

an open one. On one side, empirical support that foreigners underperform domestic investors,

due to better local knowledge, appears in Brennan and Cao (1997), Hau (2001), Choe et al

(2005), Dvorak (2005), Kalev et al (2008) and Agarwal et al (2009). On the other side, studies by

Grinblatt and Keloharju (2000), Seasholes (2004) and Froot and Ramadorai (2008) make a case

that foreigners do better than local investors, since foreign investors have a significant amount of

investment experience.

These ‘seemingly contradictory findings’ (Froot & Ramadorai, 2008) usually rely on one

main argument: information asymmetry. Whichever investor group knows more about the stocks

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makes more money. If domestic investors know more about the local market, then they are at an

advantage in timing their investment decisions. This is justified by their linguistic, cultural and

geographic proximity to the local market (Hau, 2001), their better evaluation of the local firms’

governance structure (Leuz et al, 2010) and lower costs of trade (Parwada et al, 2007). However,

if foreign investors have more expertise in trading and larger portfolios, they can employ this to

profit from trading in small or emerging markets, where domestic investors are not very

sophisticated or experienced.

The discussion on information asymmetry between foreign and domestic investors is an

important one in finance. Gehrig (1993), Brennan and Cao (1997), Kang & Stulz (1997) and Van

Nieuwerburgh & Veldkamp (2009) all emphasize informational asymmetry in their theoretical

model explaining the concentration of portfolio investment in domestic assets resulting in what is

known as the "home equity bias”. The underlying assumption behind these theoretical models is

that domestic investors apriori know more about stocks trading on their local exchanges, and

even choose to remain uninformed about foreign stocks, ‘since they profit more from knowing

information others do not know’. (Van Nieuwerburgh and Veldkamp, 2009). However, assuming

an information structure in which domestic investors know more than foreign one is not

undisputed, as Seasholes (2004) stands against the underlying assumption that domestic investors

are better informed in theoretical models of information asymmetry.

This study seeks to contribute to this line of research by answering the research question of

which investor group, domestic or foreign, performs better, and directly testing the information

asymmetry hypothesis as the reason behind this performance. As Hau (2001) warns, although

‘information asymmetry between investors can be indirectly inferred from asset allocation

decisions ……to learn more about information asymmetry, we must look directly at investment

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profitability’. Thus, in this study we perform a direct empirical analysis involving high frequency

intraday dataset from the Egyptian Stock Exchange (EGX). The EGX provides an ideal setting

for answering this controversial question: it is a good example of a country where information

asymmetry might be high: the local language is Arabic, the political setting is different than

foreign ones, it has different trading days than international stock markets and finally it is an

open and highly liberal stock market that has no impediment to foreign investment.

Several aspects of the data and methodology employed in this study contribute to the

existing literature on trading performance. First, our dataset overcomes the data limitations of

previous studies by including both transaction and ownership records for a large number of

observations (over 270 million) across over 50 different companies and a considerably long time

frame (2004-2009). We have company level high frequency transaction data which includes

prices, volumes, anonymous but unique code for each buyer and seller for each trade as well as

their nationality, type and broker. The transaction level data is combined with ownership records,

overcoming the data limitations in Hau (2001) and Dvorak (2005) and allowing us to track actual

trading profits of the various investor groups across the sample period.

When assessing trading performance we try to complement our current understanding of

the link between trading performance and information asymmetry. So far little studies provide a

concrete link between performance and information asymmetry, since this can only be achieved

by isolating the nature of differential information between the two groups. Kalev et al (2008)

attempt to do so by dividing stocks into different information levels depending on whether they

are foreign-listed or not. In addition to dividing our companies to cross-listed and foreign listed,

we further extend that by dividing our investor groups into Domestic, Arab and Non-Arab

(foreign). Our categorization allows us to capture any differences in trading performance that can

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arise from cultural, geographical or language barriers by dividing foreign investors to Arab and

Non-Arab. We further divide them by type into individual or institutional which can affect the

information level and processing capability of the investor (Aragon et al, 2007). Studies so far

suggest that individual investors are generally poor performers of equity trading (Barber et al.,

2009) suggesting that a complete analysis on whether foreigners or domestic investors perform

better should control for the type of investor.

In measuring trading performance, we combine two main methodologies in the literature

that assess performance on different levels. We measure short term trading performance using

the ‘relative price ratios’ introduced in Cho et al (2005). In this methodology, an investor group

is considered better in trading if they can on average buy (sell) stocks at lower (higher) prices

than the value weighted average price of the trading day. However, this measure short term

trading performance is in no way an indication of the ability of a certain group in making more

money over their investment horizon. We therefore use two established methods for measuring

long term performance: cumulative returns (Grinblatt and Titman, 1993) and trading profits

(Dvorak, 2005). Both measures can better assess the market timing capabilities of certain

investor groups in managing their investments to achieve higher (lower) cumulative returns

(losses) or trading profits (losses).

Our results so far indicate the following. Domestic institutional investors in the short term

trade at significantly better prices than all other categories for single listed stocks, but only

outperform foreign investors for cross-listed stocks. Domestic individuals and Non-Arab

investors are at the most disadvantage in executing trades at favorable prices, especially for

single listed stocks, in comparison to Domestic institutions and Arab investors. The result of the

long term analysis shows a different picture. Foreign institutional investors show significantly

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more superior cumulative returns in the long term for both cross-listed and single listed stocks.

Moreover, foreign and domestic institutions rank the higher in terms of making on average the

most (least) total profits (loss) per year from trading both stock categories. This shows the

importance of expertise over local knowledge in trading performance.

This paper is organized as follows. Section 2 presents the methodology employed to assess

trading performance across various investor groups. Section 3 gives an overview of the dataset

and descriptive statistics. The main results of the paper are presented in Section 4. Finally,

Section 5 gives the main conclusions of this study and possible extensions to the current work.

2. Methodology

In assessing trading performance we use three standard measures from the literature: Relative

Price Ratios (Choe et al, 2005), Cumulative Returns (Grinblatt and Titman, 1993) and Trading

Profits (Dvorak, 2005). The analysis will further use a set of ‘identifying variables’ to

distinguish between investor performance and profits by the size of broker they use, as well as by

the information environment of the company invested in by identifying companies on single or

cross-listed (Kalev et al, 2008). The identifying variables help us test the information hypothesis,

such as whether clients of big brokerages have an information advantage because of the superior

advice that they receive and thus perform better or whether foreign investors’ performance is

better for international cross-listed versus solely local single listed companies due to the better

information coverage on the former group of stocks.

2.1. Relative Price Ratios

Our first level of analysis will use the intraday trading data to compare between the short term

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trading performances of the different investor groups. We use the relative price ratio used by

Choe et al (2005) and Kalev et al, (2008). This measures compares the daily volume weighted

price by which each investor group buys (sells) relative to the overall value weighted average

price of that day to compute a relative price ratio. The investor group that buys (sells) at a

lower(higher) price to the overall VWAP of the day is assumed to have better trading

performance. Calculating relative price ratios for each group involves the following steps:

(1) Calculate a Daily Volume Weighted Average Price (VWAP) by computing a volume

weighted average price for each stock using the intraday transaction data as follows:

Aid=

∑t

Pidt V i

dt

∑t

V idt where

Pidt

refers to the price for stock i on day d for trade t, and

Vidt

refers to the

volume for stock i on day d for trade t.

(2) Calculate the Buying & Selling Weighted Average Price by each Investor group on each

stock

Bi , jd =

∑t

Pijdt V ij

dt

∑t

V ijdt where j refers to the investor group

Si , jd =

∑t

Pijdt V ij

dt

∑t

V ijdt where j refers to the investor group

(3) Compute Buy/Sell Relative Price Ratio for each investor group as follows

Bi , jd

A i ,d is a buy ratio calculated for each investor group j for each day for every stock.

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S i , jd

A i ,d is a sell ratio calculated for each investor group j for each day for every stock.

A buy (sell) ratio of less (more) than 1 indicates that an investor group pays (receives) less

(more) than the average daily price and vice versa. Everything else equal, a group of investor is

disadvantaged relative to another for purchases if investors of the first group buy at a higher

price than the investors of the second group. Similarly, a group of investor that sells at a lower

price than another group of investor is at a disadvantage relative to that group of investor. The

difference between the buy (sell) price ratios of each investor group is then computed and subject

to a t-test for significance to assess whether a certain group of investor trade at statistically

different price to the other for purchases and sales.

We calculate the relative price ratios on two levels. First, by comparing investor groups by their

nationality: Domestic, Arab, Non-Arab (j=3) and second, by comparing investor groups by both

nationality and investor type (institutional, individual) (j=6).

2.2. Cumulative Returns

To compare trading performance of the different investor across a longer time horizon, we

employ the cumulative return measure of Grinblatt & Titman (1993):

CR j=∑t=1

T

(Purc h asest−1−Salest−1

Purc hasest−1+Salest−1¿) Rt ¿

CRi is cumulative return over each period (taken as one year) by investor group j, Purchasest-1

indicates the amount bought each day by a specific investor group, Salest-1 indicates amount sold

each day by a specific investor group and Rt is return on stock following the trade ratio. This

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measure of cumulative return indicates the market timing capability of an investor group in

predicting future market movements to point out the ultimate winners and losers from trading.

2.3. Trading Profits

We finally use the trading profits of Hau (2001) and Dvorak (2005) to measure trading profits

that each group of investor makes to assess which group performs better in the market. Trading

profits ∏t+1 are calculated per transaction as:

∏t+1 = Qt ∆Pt+1

where, Qt is the stock holdings at time t, ∆Pt+1 is the share price increase between t and t+1,

where t refers to a market transaction.

The profits estimated from this equation can be market to market each time a stock trades, and

can be used to estimate the profits for each group of investor. The trading profits are then

aggregated across different spectrums from short (daily), medium (weekly) and long-run

(monthly) trading. As Dvorak (2005) explains: “This decomposition may help in understanding

the nature of the information asymmetries that may exist. For example, when domestic investors

have short-lived inside information, they should have greater short-term profits, while superior

stock picking ability should lead to long-term profits.”

One major limitation of the works of Hau (2001) and Dvorak (2005) in using the above measure

of trading profits is their lack of data on initial portfolio holding , Q0 which helps them to

properly track trading profits. We overcome this limitation in the current study by combining

intraday transaction data with initial ownership holdings for the companies analyzed.

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3. Data and Descriptive Statistics

The setting for the study is the Egyptian Stock Exchange (EGX), an emerging market that in the

past 2 decades has undergone several liberalization measures making it attractive for foreign

investment for many years up until the Arab spring uprising in January 2011. The time period of

this study cover the 6 years from 2004-2009, a period in which the EGX was considered one of

the world’s best performing stock exchanges (Saleh, 2004) and is the Middle East's second-

largest stock market by market capitalization after Saudi Arabia. (Guest, 2008), averaging

around $90billion at the end of our sample in 2009, which compares well with other emerging

markets studied in the literature.

The EGX presents a good setup for our research question for several notable reasons. First of all,

EGX attracts a large number of foreign investors who contribute as high as 32% of trading value

during our sample period, which insures sufficient foreign presence in the data to warrant

reliable results. Second, the Egyptian stock exchange does not have any restrictions on foreign

ownership of local stocks and provides several incentives for foreign ownership including tax

breaks on capital gains and dividends. Third, the EGX provides a good setup to dissect foreign

investors into more groups, mainly Arab foreign investors as well as other foreign investors. This

provides an interesting point of analysis since Arabs have similar language and culture to

Egyptians, making them a good mediating group to compare their performance to other Non-

Arab foreign investors and analyze the information asymmetry hypothesis. Finally, some of the

stocks trading on the EGX are foreign listed as global depository receipts (GDRs) on the London

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Stock Exchange (LSE) providing an excellent opportunity to distinguish the information

characteristics of the different stocks as in Kalev et al (2008).

The dataset used in our study presents a unique chance to test our research question since it is a

complete and comprehensive one. It relies on a large data set for 46 stocks1 that make up over

40% of the market capitalization of the EGX during the sample period which are presented in

Table (1). One of the merits of the dataset is its relative balance. It covers a long period of time

from January 2004-October 2009, and thus takes into consideration two important periods: 2004-

2005 when EGX was considered one of the best performing exchanges worldwide and 2008, the

crisis year, and thus time period is sufficiently spread to take into consideration different cycles

in the life of any exchange.

This complete dataset for that we will analyze relies on two major sources of data obtained from

the Egyptian Clearing House (MCSD). First, we obtain EGX’s complete intraday transaction

records for the 46 stocks for the approximately 6 year period from Jan 2004-October 2009 with

close to 30 million transactions. A typical transaction record of the data set includes the

following 14 vector columns: Date of Trade, Sequence of Trade, Stock Name, Price, Quantity,

Seller unique but anonymous code, Seller Nationality, Seller Type, Seller Broker, Buyer unique

but anonymous code, Buyer Nationality, Buyer Type, Buyer Broker. This is one of the most

comprehensive data sets in the literature, containing information on type of investor (as in Choe

et al (2005)), the broker of each investor (as in Dvork (2005) and Agrawal et al (2008)) and the

specific nationality of each investor. Moreover, the dataset is complemented by having data on

1 Stocks selected fulfilled the following criteria (1) most active by numbers and size of trade (2) were listed for at least 3 out of the 6 years and (3) traded by three nationalities of investors groups

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the holdings of all investor groups of each stock in the sample at the onset of our analysis period.

This allows us to overcome the problems in Hau (2001) and Dvorak (2005) of assuming specific

ownership values and thus to be able to calculate accurate profits for each investor group rather

than hypothetical/assumed ones.

Table (2) presents the percentage ownership of the different investor groups in our sample across

the sample period, for all the sample as well as by classification of companies into cross-listed

and single listed. Non-Arab (foreign) institutions are the largest group outside of domestic

investors owning Egyptian listed companies. On average, over 50% of cross-listed companies

are owned by Non-Arab (foreign) institutions, while single listed companies are mostly owned

by domestic institutions and only 9% owned by Non-Arab (foreign) institutions. In light of the

apparent difference in ownership between the cross-listed and single listed companies, we would

like to compare the trading performance between the investor groups across both stock

categories.

Table (3) presents a summary of the trading statistics across the sample. Domestic individuals

dominate the number of trades and proportion of value trading. This is consistent with individual

trader behavior presented in Barber et al (2009). On the other hand, Arab and Non-Arab

institutional investors, while trading less frequently than domestic investors, their average trade

size is much larger. This gives an indication of the trading behavior of institutional investors in

general, and foreign ones in particular, who execute more strategic trades reflecting their

disciplined portfolio management approach.

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4. Main Results

4.1. Relative price ratio

Tables 4 and 5 present the results across the sample for buy and sell ratios. Domestic institutions

outperform all other investor groups by buying at significantly lower prices and selling at

significantly higher prices than all other investor groups. Foreign institutional investors are the

worst performers, buying at higher and selling at lower prices than other groups. They even

perform worse than foreign individuals, an observation that goes contrary to Arab and Domestic

investors, in which institutions perform much better than individual investors. There seems to be

no consistent differences amongst short term trading performance between individual investors

of different nationalities.

How can we explain the results of the short term trading performance? Since the result is

consistent in both stock categories, this indicates that the difference in trading at better prices

across the trading day is due to short term dynamics and factors. One of those is the size of

broker being used to execute the trade. We divide the trades by broker, by classifying brokers

into two categories: Large and Small. The large brokers are those that consistently dominate a

third of market activity. Foreign institutions mostly rely on those brokers in executing their

trades. On the other hand, we find that domestic institutions and individuals rely mostly on small

brokers. The reliance of domestic institutions on small brokers for trade execution is a result of a

legal requirement by the Egyptian financial services authority to limit the trades of domestic

financial institutions though their own brokerages to 30% of their executed trades.

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We find that for cross-listed companies, Table (6), there are no significant differences in

performance between large and small brokers. However, the interesting result is for single listed

companies, in which small brokers buy (sell) at significantly lower (higher) prices than large

brokers. This might be attributed to the ability of small brokers to execute smaller and better

timed deal within the trading day.

4.2. Cumulative returns

The results of short term trading performance using price ratios can at best indicate the ability of

certain investor groups to use their market knowledge and presence as well as technical trading

rules to execute deals at favorable prices and profit from short term trades. This is in no way a

conclusive indication of their better trading performance since foreign institutional investors like

pension funds and international money managers can have longer term horizons and rely on

more fundamental trading strategies and therefore their trading performance assessment

measures are usually longer term metrics. We use in this section cumulative returns and in the

next section trading profits to assess longer term trading performance.

Table (7) present the cumulative returns for different investor groups across stock categories and

years. The result is very different from the short term performance dynamics. Foreign institutions

attain on average much higher aggregate cumulative performance for both cross-listed and single

listed stocks and for the majority of sample period. On average, the make an approximate annual

cumulative return of 23.52% for cross-listed stocks and 13.65% for single listed stocks from

2004-2009, outperforming all other investor group categories. Domestic individual and

institutions are surprisingly the worst performers across the sample period and across stock

categories, having on average cumulative loss of -5.36% and -9.22%.

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4.3. Trading profits

In terms of size of profits, Table (8) presents the annual total profits by each investor group

across stock categories and sample period and Table (9) presents the profits per trade executed.

Individual investors on average achieve the least profits with the exception of 2006 and 2008, in

which individual investors outperformed institutional investors. This shows that individual

investors hold better during crisis periods. Non-Arab Foreign institutional investors achieved the

largest profits across the sample followed by Arab investors, but the result is asymmetric across

time periods.

5. Conclusions

This paper studies the trading performance of various investor groups on an emerging markets.

We find that in the short term, domestic institutional investors trade at significantly better prices

than all other categories for single listed stocks, but only outperform the non-Arab foreign

investor category for cross-listed stocks. This trend is reversed in longer term performance, since

non-Arab foreign institutional investors show more superior cumulative returns and profits. The

domestic individual category is the loser on all accounts despite their domination of the overall

size and value of trading on the stock market consistent with evidence in [Barber, B. M., Lee, Y.

T., Liu, Y. J., & Odean, T. (2009). Just how much do individual investors lose by trading?

Review of Financial Studies, 22(2), 609-632.] This sheds light on the importance of expertise

over local knowledge in trading performance. One important outcome of our results is to

encourage the role of market authorities in education of small domestic investors on rational

trading since they are the group with the most consistent losses both short and long term.

14

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Table 1 Sample Companies

Stock Ticker IndustryExchanges

listedProportion of Total Market Cap

2004 2005 2006 2007 2008 2009Egyptians Abroad ABRD Financial services EGX 0.01% 0.01% 0.01% 0.01% 0.01% 0.02%Arab Cotton Ginning ACGC Household products EGX 0.10% 0.26% 0.13% 0.07% 0.05% 0.07%Al Ahly for Development and Investment AFDI Financial services EGX 0.03% 0.08% 0.06% 0.04% 0.10% 0.10%Alexandria Mineral Oils co AMOC Oil and Gas EGX 1.47% 1.27% 0.87% 0.87% 0.65%Arab Polvara Spinning and Weaving Company APSW Household products EGX 0.10% 0.14% 0.07% 0.05% 0.04% 0.07%Credit Agricole Egypt CIEB Banks EGX 0.08% 0.13% 0.03% 0.07% 0.04% 0.05%Commercial International Bank (Egypt) COMI Banks EGX, LSE 2.10% 1.65% 2.11% 2.27% 2.26% 3.44%Canal Shipping Agencies Co CSAG Industrial Goods EGX 0.37% 0.38% 0.38% 1.09% 0.35% 0.51%National Bank for Development (Egypt) DEVE Banks EGX 0.08% 0.06% 0.09% 0.13% 0.06% 0.10%El Ezz Ceramics and Porcelain Co (Gemma) ECAP Construction EGX 0.07% 0.15% 0.07% 0.08% 0.04% 0.06%Egyptian Financial and Industrial EFCO Chemicals EGX 0.11% 0.14% 0.08% 0.13% 0.05% 0.06%Egyptian Resorts Company EGTS Travel EGX 0.04% 0.02% 0.13% 0.06% 0.03% 0.04%Egyptians for Hous, Develop and Recon. EHDR Real estate EGX 0.00% 0.01% 0.01% 0.03% 0.05% 0.10%Egypt Kuwait Holding Co (SAE) EKHO Financial services EGX, KSE 0.65% 0.10% 0.14% 0.11% 0.11% 0.19%Electro Cable Egypt Co ELEC Industrial Goods EGX 0.03% 0.03% 0.05% 0.00% 0.01% 0.01%El Kahera for housing and Development ELKA Real estate EGX 0.02% 0.04% 0.03% 0.03% 0.02% 0.04%El Shams Housing and Urbanization SAE ELSH Real estate EGX 0.03% 0.05% 0.04% 0.04% 0.02% 0.07%

Egyptian Company for Mobile Services EMOBTelecommunications EGX 5.46% 4.43% 3.40% 2.62% 3.06% 4.22%

Egypt for Poultry EPCO Food and beverages EGX 0.00% 0.00% 0.00% 0.00% 0.00% 0.01%Al Ezz Steel Rebars Company SAE ESRS Basic resources EGX 0.85% 1.30% 0.86% 0.74% 0.48% 0.76%

Telecom Egypt SAE ETELTelecommunications EGX 7.17% 4.59% 0.47% 5.86% 6.18%

Housing and Development Bank HDBK Financial services EGX 0.04% 0.07% 0.18% 0.08% 0.09% 0.08%Heliopolis Co for Housing & Development HELI Real estate EGX 0.15% 0.33% 0.34% 0.99% 0.40% 0.55%EFG Hermes Holding SAE HRHO Financial services EGX, LSE 0.24% 1.18% 0.96% 1.46% 0.68% 1.35%Egyptian Iron and Steel Company IRON Basic resources EGX 0.02% 0.02% 0.02% 0.02% 0.02% 0.03%El Nasr Clothes and textiles Co Kabo KABO Household products EGX 0.03% 0.07% 0.02% 0.01% 0.01% 0.01%Misr Chemical Industries Co. MICH Chemicals EGX 0.10% 0.16% 0.07% 0.07% 0.05% 0.10%Nasr City Company for Housing & Development MNHD Real estate EGX 0.34% 0.39% 0.33% 0.70% 0.59% 0.65%Egyptian Media Production City co MPRC Media EGX 0.96% 0.52% 0.37% 0.26% 0.16% 0.22%Nile Cotton Ginning NCGC Household products EGX 0.01% 0.05% 0.04% 0.03% 0.10% 0.15%Sixth of October Development and Investment OCDI Real estate EGX 0.02% 0.45% 0.41% 0.46% 0.13% 0.30%Orascom Construction Industries OCIC Construction EGX, LSE 4.40% 6.85% 7.58% 10.77% 4.31% 7.71%Orascom Hotels and Development ORHD Travel EGX 0.20% 0.51% 0.66% 1.01% 0.35% 0.62%

Orascom Telecom ORTETelecommunications EGX, LSE 11.82% 14.31% 15.93% 13.45% 7.18% 8.51%

Egyptian Saudi Finance Bank SAUD Banks EGX 0.05% 0.05% 0.05% 0.05% 0.02% 0.04%Sidi Kerir Petrochemicals Co SKPC Chemicals EGX 0.49% 0.45% 1.41% 1.15% 1.08%Samad Misr EGYFERT SMFR Chemicals EGX 0.01% 0.00% 0.01% 0.01% 0.01% 0.01%

17

Alexandria Spinning and Weaving SPIN Household products EGX 0.10% 0.08% 0.31% 0.00% 0.01% 0.01%South Valley Cement SVCE Construction EGX 0.06% 0.14% 0.38% 0.12% 0.11% 0.17%El Sewedy Cables Co SWDY Industrial Goods EGX 0.53% 1.09% 1.25% 1.06%United Arab Shipping UASG Industrial Goods EGX 0.00% 0.00% 0.03% 0.08% 0.03% 0.06%Upper Egypt Contracting Co UEGC Construction EGX 0.00% 0.00% 0.01% 0.01% 0.01% 0.04%United Housing & Development UNIT Real estate EGX 0.03% 0.07% 0.05% 0.04% 0.03% 0.08%

Vodafone Egypt VODETelecommunications EGX, LSE 5.36% 5.30% 4.24% 3.01% 4.05% 5.81%

Al Watany bank of egypt WATA Banks EGX 0.13% 0.20% 0.23% 0.64% 0.62% 0.86%Extracted Oils and Derivatives Co ZEOT Oil and Gas EGX 0.01% 0.01% 0.02% 0.01% 0.02% 0.02%

Total      34.24

% 48.87% 46.79%44.68

% 34.88% 46.29%

18

Table 2 Ownership by Investor Group (%) across sample period 2004-2009 (detailed table in appendix)

  Aind Ainst Dind Dinst Find FinstAll  Mean 4.57 6.42 28.39 44.15 0.27 16.20Min 0.21 0.01 0.54 1.14 0.00 0.00Max 23.13 56.00 94.93 96.11 5.22 92.80Stdev 5.73 12.56 23.90 28.24 0.80 24.80Cross-Listed  Mean 2.04 9.85 8.30 29.25 0.15 50.40Min 0.40 0.51 0.54 1.31 0.01 2.81Max 4.87 56.00 21.80 84.22 0.36 92.80Stdev 1.55 18.92 6.93 29.00 0.11 34.10Single Listed  Mean 5.12 5.70 32.67 47.28 0.30 8.94Min 0.21 0.01 1.92 1.14 0.00 0.00Max 23.13 47.74 94.93 96.11 5.22 68.43Stdev 6.17 10.98 24.07 27.56 0.87 15.58

19

Table 3 Trading statistics across sample period 2004-2009 (detailed table in appendix)

  Aind Ainst Dind Dinst Find FinstPanel A: Number of Trades    All    Mean 4,190 2,067 97,795 6,493 485 5,121Stdev 2,047 1,026 49,927 4,210 154 2,659CrossMean 8,246 5,747 114,744 14,525 1,099 18,490Stdev 5,537 3,240 66,846 11,096 397 11,258SingleMean 3,271 1,202 93,850 4,740 342 2,180Stdev 1,832 649 57,499 2,888 181 1,151Panel B: Proportion Value TradedAllMean 6.03 4.01 68.84 12.03 0.49 8.60Stdev 2.36 1.36 5.24 3.29 0.07 2.74CrossMean 8.05 6.72 38.97 13.35 0.83 24.10Stdev 4.29 2.72 11.21 3.95 0.29 7.53SingleMean 5.48 3.40 73.98 11.67 0.41 5.07Stdev 2.21 1.66 5.24 3.75 0.09 2.04Panel C: Average Trade SizeAllMean 2,954 8,504 1,080 5,547 1,675 3,767Stdev 2,212 13,586 281 5,530 539 2,866CrossMean 2,130 3,440 850 3,475 1,598 3,461Stdev 623 2,470 244 3,093 581 1,016SingleMean 3,151 10,743 1,129 6,038 1,698 3,894Stdev 2,779 19,524 291 7,029 535 3,617

20

Table 4 Buy ratios (in %) across sample period 2004-2009 (detailed table in appendix)

  A-Ind A-Inst D-Ind D-Inst F-Ind F-InstPanel A: Buy RatioAllMean 99.96 99.92 99.96 99.85 99.93 100.07

  Difference t-stat

Ainst-Aind -0.04 -3.19Dinst-Dind -0.11 -16.54Finst-Find 0.14 9.37Dinst-Ainst -0.07 -5.93Dinst-Finst -0.22 -20.92Dind-Arabind 0.00 0.04Dind-Find 0.03 2.37CrossMean 99.97 99.98 99.95 99.89 99.94 100.07

  Difference t-stat

Ainst-Aind 0.01 0.37Dinst-Dind -0.05 -3.98Finst-Find 0.13 5.90Dinst-Ainst -0.09 -4.23Dinst-Finst -0.18 -11.17Dind-Arabind -0.03 -1.57Dind-Find 0.01 0.35SingleMean 99.96 99.89 99.97 99.84 99.93 100.08

  Difference t-stat

Ainst-Aind -0.07 -4.50Dinst-Dind -0.13 -16.05Finst-Find 0.15 7.45Dinst-Ainst -0.06 -3.80Dinst-Finst -0.24 -17.13Dind-Arabind 0.01 0.86Dind-Find 0.04 2.26

21

Table 5 Sell ratio (in %) across sample period 2004-2009 (detailed table in appendix)

  All  A-Ind A-Inst D-Ind D-Inst F-Ind F-InstPanel A: Sell RatioAllMean 100.11 100.10 100.04 100.19 100.08 99.99  Differenc

e t-statAinst-Aind -0.01 -0.99Dinst-Dind 0.15 22.06Finst-Find -0.09 -6.15Dinst-Ainst 0.09 8.15Dinst-Finst 0.20 19.27Dind-Arabind -0.07 -9.39Dind-Find -0.04 -3.36CrossMean 100.11 100.08 100.06 100.14 100.11 99.98  Differenc

e t-statAinst-Aind -0.03 -1.27Dinst-Dind 0.08 5.33Finst-Find -0.13 -5.52Dinst-Ainst 0.06 3.15Dinst-Finst 0.16 9.83Dind-Arabind -0.05 -2.54Dind-Find -0.05 -2.33SingleMean 100.11 100.10 100.03 100.21 100.07 99.99  Differenc

e t-statAinst-Aind 0.00 -0.21Dinst-Dind 0.17 21.96Finst-Find -0.08 -3.91Dinst-Ainst 0.10 7.00Dinst-Finst 0.22 15.09Dind-Arabind -0.07 -9.71Dind-Find -0.04 -2.19

22

23

Table 6 Buy and Sell Ratios (in %) by Broker Size  2004 2005 2006 2007 2008 2009  Large Small Large Small Large Small Large Small Large Small Large SmallPanel A-Buy RatioAllMean 100.05 99.97 100.10 99.97 100.00 99.88 99.98 99.93 99.95 99.91 99.90 99.92Difference (Small-Large) -0.08 -3.71 -0.13 -3.02 -0.12 -9.63 -0.06 -7.17 -0.04 -3.90 0.03 3.01CrossMean 100.07 100.03 100.18 100.12 100.01 99.91 99.96 99.93 99.94 99.90 99.93 99.95Difference (Small-Large) -0.03 0.35 -0.06 -0.48 -0.10 -4.13 -0.02 -2.27 -0.04 -2.40 0.02 1.50SingleMean 100.04 99.94 100.05 99.91 100.00 99.88 99.99 99.92 99.96 99.92 99.89 99.91Difference (Small-Large) -0.10 -5.68 -0.14 -9.29 -0.12 -8.89 -0.07 -6.83 -0.04 -3.29 0.03 2.76Panel B-Sell RatioAllMean 100.04 99.94 100.05 99.91 100.00 99.88 99.99 99.92 99.96 99.92 99.89 99.91Difference (Small-Large) -0.10 2.03 -0.14 2.73 -0.12 5.68 -0.07 5.77 -0.04 5.17 0.03 -0.65CrossMean 100.12 100.13 100.19 100.34 100.10 100.15 100.06 100.07 100.09 100.11 100.08 100.06Difference (Small-Large) 0.01 0.26 0.15 1.20 0.05 1.96 0.01 1.10 0.02 1.11 -0.03 -1.15SingleMean 100.02 100.09 100.03 100.14 100.04 100.12 100.05 100.10 100.06 100.12 100.10 100.10Difference (Small-Large) 0.07 5.12 0.11 7.05 0.08 6.05 0.06 5.68 0.07 5.16 0.00 -0.11

24

Table 7 Cumulative Returns (%) by Investor Group

Year StatsAll Companies Cross-Listed Single Listed

Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst

2004

Mean -6.93 0.85 -1.98 -8.45 1.59 17.09 -9.29 3.86 -2.86 -14.57 9.86 23.29 -6.42 -0.26 -1.82 -7.15 -1.05 15.36Min -58 -50 -40 -76 -37 -61 -50 -50 -15 -50 -23 -61 -58 -31 -40 -76 -37 -28Max 27 32 21 24 55 83 27 32 13 14 55 64 25 18 21 24 26 83Stdev 19.84 16.44 9.55 24.13 17.96 30.1 26.35 26.7 8.51 21.59 26.47 44.32 18.65 11.52 9.83 24.74 14.13 25.79Rank 5 3 4 6 2 1 5 3 4 6 2 1 5 2 4 6 3 1

2005

Mean -2.7 15.11 -2.16 -21.22 4.74 12.29 9.25 39.63 -10.75 -19.88 9.13 18.5 -5.21 8.34 -0.56 -21.49 3.71 10.79Min -58 -26 -41 -119 -70 -34 -23 2 -25 -119 -70 -5 -58 -26 -41 -106 -37 -34Max 154 89 39 40 97 62 66 89 12 40 61 55 154 55 39 32 97 62Stdev 36.55 25.04 14.83 33.81 27.35 22.23 28.18 31.67 12.71 49.23 39.38 21.12 37.91 18.34 14.78 30.77 24.39 22.54Rank 5 1 4 6 3 2 3 1 5 6 4 2 5 2 4 6 3 1

2006

Mean 1.86 14.87 -1.29 -26.09 3.67 15.09 1.78 18.22 -4.67 -34.56 -0.44 25.22 1.88 14.03 -0.58 -24.36 4.62 12.41Min -70 -36 -50 -130 -53 -40 -51 -16 -21 -114 -43 -35 -70 -36 -50 -130 -53 -40Max 101 88 40 54 78 87 74 76 10 -3 40 75 101 88 40 54 78 87Stdev 34.59 28.07 12.94 40.95 24.67 30.01 39.05 29.67 9.7 34.13 29.82 34.93 34.05 28.03 13.51 42.35 23.68 28.55Rank 4 2 5 6 3 1 3 2 5 6 4 1 4 1 5 6 3 2

2007

Mean 5.08 -4.49 -7.39 -0.18 8.55 6.02 -8.99 -12.56 -9.95 12.89 10.21 5.25 7.9 -2.84 -6.91 -2.63 8.22 6.16Min -46.88 -34.87 -133.54 -65.98 -41.13 -45.69 -39.18 -34.87 -52.2 -27.92 -22.81 -14.99 -46.88 -26.92 -133.54 -65.98 -41.13 -45.69Max 55.06 18.38 86.69 74.88 89.44 40.76 20.89 -1.12 28.93 74.88 66.98 29.88 55.06 18.38 86.69 47.79 89.44 40.76Stdev 26.08 8.97 39.18 27.1 24.83 13.83 20.81 9.73 24.79 31.15 26.84 13.87 26.31 7.95 41.51 25.9 24.72 13.97Rank 3 5 6 4 1 2 4 6 5 1 2 3 2 5 6 4 1 3

2008

Mean 4.81 1.72 -11.74 -2.76 2.96 25.47 -18.1 22.9 -27.9 8.9 -20.33 42.2 9.68 -2.79 -8.38 -5.19 7.52 21.91Min -74 -162 -47 -76 -60 -47 -72 -11 -47 -71 -56 0 -74 -162 -34 -76 -60 -47Max 92 113 12 90 84 105 36 74 12 72 6 94 92 113 10 90 84 105Stdev 37.36 42.34 14.03 37.16 33.24 38.55 36.39 31.73 16.87 46.65 21.83 32.39 36.08 43.21 10.82 34.97 33.33 39.11Rank 2 4 6 5 3 1 4 2 6 3 5 1 2 4 6 5 3 1

2009

Mean -3.68 3.21 -7.61 3.38 -5.4 17.09 2 14.11 -16.5 17.8 -9.11 26.67 -4.89 1.13 -5.72 0.38 -4.67 15.26Min -73 -88 -38 -72 -95 -50 -48 -54 -38 -27 -41 -22 -73 -88 -35 -72 -95 -50Max 71 64 5 73 99 86 28 56 1 64 99 80 71 64 5 73 69 86Stdev 29.96 35.14 11.12 30.74 31.55 28.66 19.92 34.78 13.66 27.76 43.77 30.61 31.73 35.2 9.65 30.75 29.17 28.25Rank 4 3 6 2 5 1 4 3 6 2 5 1 5 2 6 3 4 1

25

Table 8 Total Annual Profits by Investor (millions EGP)    All Companies Cross-Listed Single-Listed

    Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind DinstFind Finst

2004

Total 502 831 3812 8062 166 20212 380 730 3373 3093 79 18799 122 101 439 4968 87 1413 Mean 13 21 95 202 4 505 48 91 422 387 10 2350 4 3 14 155 3 44 Min (62) (16) (23) (51) (1) (14) (62) (16) (23) (3) (1) (3) (1) (1) (14) (51) (0) (14)Max 200 650 2944 3874 84 14932 200 650 2944 1054 74 14932 47 84 153 3874 84 1225 Stdev 39 103 465 648 17 2373 80 227 1023 457 26 5129 11 15 34 685 15 217 Rank 5 4 3 2 6 1 5 4 2 3 6 1 4 5 3 1 6 2

2005

Total 3647 3091 11465 31193 264 62176 2420 2665 7023 17906 221 58041 5870 5125 21872 52875 484 102782 Mean 81 69 255 693 6 1382 303 333 878 2238 28 7255 140 122 521 1259 12 2447 Min (2) (61) (23) (14) (2) (4) (2) (61) (23) (14) (0) (4) (2) (61) (23) (14) (2) (4)Max 761 1379 4984 6240 150 29876 761 1379 4984 6240 150 29876 3647 3091 11465 31193 264 62176 Stdev 156 222 749 1476 23 5217 251 459 1673 2438 51 11069 569 516 1896 4899 46 10524 Rank 4 5 3 2 6 1 5 4 3 2 6 1 4 5 3 2 6 1

2006

Total (536) (1436) (6261)(10297

)(117

) (16244) (234)(1316

)(5227

) (9689)(101

) (15508) (302) (120)(1034

) (608) (16) (737)Mean (12) (31) (136) (224) (3) (353) (29) (165) (653) (1211) (13) (1938) (8) (3) (27) (16) (0) (19)

Min (211) (1306) (3703) (7433)(103

) (21730) (211)(1306

)(3703

) (7433)(103

) (21730) (153) (54) (473) (1746) (8) (600)Max 239 149 310 1007 5 7446 239 149 19 158 5 7446 76 47 310 1007 2 139 Stdev 64 197 572 1151 15 3413 141 471 1277 2546 37 8446 33 20 139 362 2 109 Rank 2 3 4 5 1 6 2 3 4 5 1 6 3 2 6 4 1 5

2007

Total 789 (11) (398) 16297 (156

) 5747 1017 (126)(4957

) 12745 (152

) (725) (228) 115 4559 3551 (5) 6472 Mean 17 (0) (9) 354 (3) 125 127 (16) (620) 1593 (19) (91) (6) 3 120 93 (0) 170

Min (569) (1905) (6034) (7700)(208

) (51669) (18)(1905

)(6034

) (286)(208

) (51669) (569) (305)(1102

) (7700) (19) (324)Max 461 886 6909 9817 48 40810 461 886 509 9817 48 40810 320 300 6909 6105 12 3087 Stdev 147 334 1396 2219 32 9869 190 821 2198 3347 78 24985 127 89 1166 1861 4 578 Rank 3 4 6 1 5 2 2 3 6 1 4 5 6 4 2 3 5 1

2008 Total

(3142)

(10603)

(16242)

(49660)

(329)

(152525)

(1164)

(5719)

(7837)

(17134)

(321)

(140921)

(1978)

(4884)

(8405)

(32525) (8)

(11604)

Mea (68) (230) (353) (1080) (7) (3316) (145) (715) (980) (2142) (40) (17615) (52) (129) (221) (856) (0) (305)26

n

Min (888) (3186) (6271) (8473)(236

) (61004) (622)(2002

)(6271

) (7140)(236

) (61004) (888)(3186

)(4323

) (8473) (9) (5872)Max 36 14 255 71 22 3 0 (2) (0) 33 1 (34) 36 14 255 71 22 3 Stdev 171 593 1098 2057 37 12486 255 723 2152 2403 84 26722 147 517 698 1938 4 995 Rank 2 3 4 5 1 6 2 3 4 5 1 6 2 3 4 6 1 5

2009

Total 888 3429 2354 17718 71 37796 410 897 1244 9741 62 35034 478 2532 1110 7978 9 2761 Mean 19 75 51 385 2 822 51 112 155 1218 8 4379 13 67 29 210 0 73 Min (7) (7) (287) (493) (3) (189) (0) 9 (18) 65 (0) 22 (7) (7) (287) (493) (3) (189)Max 243 2005 719 4825 34 16590 243 253 719 4404 34 16590 241 2005 196 4825 6 1360 Stdev 53 297 127 1006 6 2736 92 83 245 1477 14 5492 40 325 74 798 1 290 Rank 5 3 4 2 6 1 5 4 3 2 6 1 5 3 4 1 6 2

27

Table 9 Profit per Trade

  Nationality and Type Nationality Type      Aind Ainst Dind Dinst Find Finst Arab Domestic Foreign Individual Institutional

All

2004 Total 472,255 2,282,508 158,903 4,137,965 733,476 9,124,649 2,754,763 4,296,868 9,858,125 4,769,124 15,545,121Rank 5 3 6 2 4 1 3 2 1 2 1

2005 Total 1,213,973 2,129,922 222,954 2,191,299 609,295 17,770,924 3,343,896 2,414,254 18,380,219 3,628,227 22,092,146Rank 4 3 6 2 5 1 2 3 1 2 1

2006 Total -83,067 -443,472 -58,804 -2,583,898 -219,362 -4,247,981 -526,539 -2,642,702 -4,467,342 -2,725,769 -7,275,351Rank 2 4 1 5 3 6 1 2 3 1 2

2007 Total 136,553 -4,845 -3,291 3,094,687 -271,318 1,147,056 131,708 3,091,396 875,738 3,227,949 4,236,897Rank 3 5 4 1 6 2 3 1 2 2 1

2008 Total -579,021 -3,815,917 -104,647 -7,573,065 -482,563 -15,779,298 -4,394,939 -7,677,713 -16,261,861 -8,256,734 -27,168,280Rank 3 4 1 5 2 6 1 2 3 1 2

2009 Total 259,563 1,463,940 18,273 2,543,798 153,758 5,805,498 1,723,503 2,562,072 5,959,257 2,821,635 9,813,237Rank 4 3 6 2 5 1 3 2 1 2 1

All Total 236,710 268,689 38,898 301,798 87,214 2,303,475 505,399 340,696 2,390,689 577,405 2,873,962Rank 4 3 6 2 5 1 2 3 1 2 1

Cross

2004 Total 133,082 931,929 63,826 549,054 150,320 3,084,182 1,065,010 612,880 3,234,502 745,962 4,565,165Rank 5 2 6 3 4 1 2 3 1 2 1

2005 Total 304,744 663,007 84,608 490,789 203,016 4,856,459 967,751 575,397 5,059,475 880,142 6,010,255Rank 4 2 6 3 5 1 2 3 1 2 1

2006 Total -12,591 -129,365 -21,367 -915,507 -58,123 -1,293,328 -141,956 -936,874 -1,351,452 -949,465 -2,338,201Rank 1 4 2 5 3 6 1 2 3 1 2

2007 Total 108,891 -25,005 -46,107 1,371,753 -150,790 -43,137 83,886 1,325,646 -193,928 1,434,537 1,303,611Rank 2 3 5 1 6 4 2 1 3 1 2

2008 Total -210,141 -840,096 -85,848 -1,530,598 -332,243 -3,962,004 -1,050,237 -1,616,446 -4,294,247 -1,826,587 -6,332,698Rank 2 4 1 5 3 6 1 2 3 1 2

2009 Total 78,331 117,178 11,394 697,512 48,365 1,228,376 195,509 708,906 1,276,741 787,237 2,043,066Rank 4 3 6 2 5 1 3 2 1 2 1

All Total 67,053 119,608 1,084 110,501 -23,243 645,091 186,661 111,585 621,848 178,638 875,200Rank 4 2 5 3 6 1 2 3 1 2 1

Single

2004 Total 189,004 527,333 24,077 4,565,625 662,548 1,366,582 716,337 4,589,702 2,029,130 4,778,706 6,459,540Rank 5 4 6 1 3 2 3 1 2 2 1

2005 Total 3,186,154 7,757,350 490,472 5,610,718 1,911,264 78,014,214 10,943,504 6,101,191 79,925,478 9,287,345 91,382,282Rank 4 2 6 3 5 1 2 3 1 2 1

2006 Total -82,033 -79,778 -13,803 -245,521 -64,099 -447,421 -161,812 -259,324 -511,520 -341,358 -772,720Rank 4 3 1 5 2 6 1 2 3 1 2

2007 Total -45,440 70,480 36,871 803,759 -9,844 2,563,793 25,039 840,630 2,553,949 795,190 3,438,032Rank 6 3 4 2 5 1 3 2 1 2 1

2008 Total -366,109 -2,560,461 -49,834 -5,827,694 -12,305 -2,754,337 -2,926,570 -5,877,528 -2,766,642 -6,243,637 -11,142,492Rank 3 4 2 6 1 5 2 3 1 1 2

2009 Total 157,834 1,934,058 8,343 1,463,295 29,741 1,176,949 2,091,893 1,471,638 1,206,690 1,629,472 4,574,302Rank 4 1 6 2 5 3 1 2 3 2 1

All Total 506,568 1,274,830 82,688 1,061,697 419,551 13,319,963 1,781,399 1,144,385 13,739,514 1,650,953 15,656,491Rank 4 2 6 3 5 1 2 3 1 2 1

28

Appendix Tables

29

Table 10 Ownership by Investor Group by Year

2004 2005 2006  Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find FinstAll        Mean 3.61 3.36 25.78 50.87 0.25 16.13 4.68 4.50 28.06 48.35 0.32 14.09 4.71 4.85 32.78 42.17 0.29 15.19Min 0.00 -0.05 0.82 1.61 0.00 0.00 0.00 0.00 0.92 0.00 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.00Max 60.62 65.77 93.96 96.80 5.15 91.07 32.92 58.95 99.82 96.77 5.31 89.27 62.67 55.83 97.85 95.53 5.20 91.97Stdev 9.98 12.09 23.31 30.02 0.84 26.76 6.66 11.17 26.82 31.34 0.85 23.88 10.47 11.08 28.81 32.83 0.80 24.74Cross-Listed        Mean 2.50 10.83 9.89 21.53 0.12 55.13 4.40 11.05 10.10 32.38 0.18 41.89 3.05 10.21 13.60 29.01 0.18 43.96Min 0.27 0.00 0.82 1.61 0.00 0.63 0.85 0.90 0.92 1.93 0.01 2.40 0.00 0.10 0.15 0.48 0.00 0.64Max 5.09 65.77 22.29 63.65 0.36 91.07 12.99 58.95 22.99 81.90 0.41 89.27 7.87 55.83 36.64 84.85 0.47 91.97Stdev 1.62 24.25 7.36 21.64 0.13 33.41 3.77 19.80 7.07 27.99 0.15 33.55 2.95 18.80 13.56 30.60 0.16 35.70Single Listed        Mean 3.83 1.87 28.96 56.74 0.27 8.33 4.74 3.09 31.94 51.81 0.35 8.08 5.06 3.72 36.82 44.94 0.32 9.14Min 0.00 -0.05 1.92 1.67 0.00 0.00 0.00 0.00 2.06 0.00 0.00 0.00 0.00 0.00 1.64 0.00 0.00 0.00Max 60.62 45.06 93.96 96.80 5.15 75.05 32.92 47.84 99.82 96.77 5.31 75.05 62.67 47.84 97.85 95.53 5.20 77.99Stdev 10.93 7.66 24.15 28.13 0.92 17.04 7.17 8.04 27.97 31.29 0.93 16.41 11.44 8.66 29.63 32.99 0.87 16.93

2007 2008 2009  Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find FinstAll        Mean 6.37 8.39 26.74 40.18 0.31 17.99 3.92 8.86 27.96 42.22 0.30 16.74 4.15 8.54 29.01 41.11 0.16 17.08Min 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Max 67.22 99.73 99.29 95.95 4.83 95.85 28.06 99.84 99.24 95.53 2.59 95.23 27.63 99.84 89.22 95.53 2.50 95.83Stdev 12.05 19.05 28.38 31.14 0.77 27.90 6.57 20.89 30.83 32.56 0.56 27.51 6.83 20.04 30.67 32.37 0.41 27.99Cross-Listed        Mean 0.92 7.27 6.14 31.18 0.16 54.32 0.77 10.52 5.59 30.59 0.13 52.40 0.60 9.23 4.49 30.83 0.12 54.73Min 0.00 0.10 0.00 0.35 0.00 2.61 0.00 0.09 0.00 1.69 0.00 6.14 0.00 0.00 0.00 2.19 0.00 7.79Max 5.16 38.16 20.46 84.27 0.34 95.85 5.06 62.28 18.02 84.96 0.37 93.90 3.63 61.29 12.12 85.86 0.36 95.83Stdev 1.75 12.69 7.12 30.73 0.15 36.49 1.75 21.03 6.75 28.96 0.16 34.74 1.25 21.11 5.50 29.63 0.15 35.30Single Listed        Mean 7.55 8.64 31.20 42.13 0.35 10.14 4.60 8.50 32.80 44.74 0.34 9.02 4.91 8.39 34.32 43.34 0.17 8.94Min 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Max 67.22 99.73 99.29 95.95 4.83 90.50 28.06 99.84 99.24 95.53 2.59 95.23 27.63 99.84 89.22 95.53 2.50 94.99Stdev 13.00 20.30 29.32 31.30 0.85 18.33 7.03 21.13 31.89 33.10 0.61 18.61 7.30 20.10 31.32 32.89 0.44 18.23

30

Table 11Trading Statistics 2004-2006

  2004 2005 2006  Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst

Panel A: Number of TradesAll    

Mean 1,063 364 23,989 1,948 226 2,215 3,004 1,451 51,42314,23

5 433 3,499 6,455 3,238 106,469 3,985 531 3,824

Stdev 1,853 408 39,051 3,076 317 4,058 4,056 1,859 69,96550,44

1 634 7,097 11,254 5,595 174,089 5,368 1,247 5,579Cross    

Mean 2,858 784 52,852 5,634 524 6,095 7,942 4,020 83,00636,48

5 1,087 11,951 18,568 10,174 244,631 10,583 1,730 11,991

Stdev 1,626 228 41,885 4,227 372 4,069 4,966 1,915 71,63785,29

8 949 10,269 19,328 9,303 309,134 8,641 2,461 5,778Single    Mean 645 192 18,216 1,088 132 1,034 1,842 661 44,594 9,424 253 1,317 3,687 1,505 74,889 2,477 249 1,646

Stdev 1,661 333 36,381 2,002 236 3,308 2,811 879 68,66939,51

1 368 3,903 6,094 2,080 110,658 2,763 466 2,889Panel B: Proportion Value Traded

All    Mean 2.87 3.45 72.45 15.45 0.43 5.35 9.22 3.18 66.81 13.39 0.54 6.85 7.35 6.72 61.8 15.05 0.54 8.54Stdev 2.54 11.93 28.41 23.11 0.8 10.05 12.56 4.41 26.01 16.17 0.65 12.73 5.38 15.11 28.9 19.6 0.82 15.49Cross    Mean 2.48 1.5 22.97 10.1 0.55 14.53 11.34 7.72 42.12 16.38 1.34 21.11 11.06 7.19 45.82 12.82 0.67 22.44Stdev 5.55 2.31 58.04 12.68 0.89 20.53 4.32 4.04 19.45 20.52 0.99 17.87 4.64 3.16 28.4 9.19 0.36 23.2Single    Mean 2.34 3.68 75.33 16 0.33 2.32 8.76 2.2 72.15 12.75 0.37 3.77 6.48 6.61 65.57 15.57 0.51 5.27Stdev 2.22 13.08 28.79 24.98 0.81 5.25 13.71 3.88 24.26 15.34 0.39 9 5.23 16.77 28.1 21.4 0.9 11.23

Panel C: Average Trade SizeAll    

Mean 1,415 36,229 85016,71

7 1,109 2,453 7,379 2,566 979 3,586 1,438 2,307 1,819 2,886 933 3,220 1,524 9,601

Stdev 1,069 157,130 82964,40

3 693 2,783 37,793 2,311 1,366 9,298 1,391 2,205 1,678 5,584 1,008 5,225 1,682 41,353Cross    Mean 1,181 1,351 715 1,231 1,019 3,066 1,565 2,659 666 1,378 1,195 2,420 2,319 2,099 685 4,718 1,246 3,771Stdev 800 636 419 615 616 2,735 813 3,460 351 689 539 2,523 2,236 1,367 392 8,012 763 6,169Single    

31

Mean 1,470 50,591 87720,33

1 1,138 2,266 8,747 2,537 1,047 4,063 1,505 2,278 1,701 3,082 992 2,867 1,591 11,266

Stdev 1,127 186,386 89071,25

6 726 2,831 42,004 1,923 1,49310,21

1 1,547 2,161 1,537 6,214 1,101 4,430 1,839 46,840

32

Table 12 Trading Statistics 2007-2009

  2007 2008 2009  Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst Aind Ainst Dind Dinst Find Finst

Panel A: Number of TradesAll      

Mean 5,774 2,229 120,852 5,266 577 5,010 5,426 2,779155,20

3 6,557 681 9,666 3,420 2,342 128,832 6,965 462 6,510

Stdev 5,941 2,771 101,373 5,359 529 8,000 4,220 2,960131,86

3 4,901 650 15,660 2,498 2,831 102,030 6,324 564 11,624Cross      

Mean 9,338 5,043 107,515 9,291 1,006 16,816 5,539 6,807 91,285 11,195 966 35,568 5,230 7,655 109,17113,96

5 1,284 28,521Stdev 8,093 3,896 108,486 5,422 731 12,241 4,737 4,045 50,343 5,654 313 22,064 3,675 2,456 83,701 7,621 904 12,014Single      

Mean 5,024 1,636 123,660 4,419 486 2,524 5,402 1,908168,65

9 5,581 627 4,213 3,029 1,309 133,084 5,452 303 2,346

Stdev 5,216 2,096 101,120 5,013 437 3,605 4,172 1,773139,99

5 4,188 685 5,527 2,028 1,357 106,097 4,935 285 5,030Panel B: Proportion Value Traded

All      Mean 7.25 3.96 70.72 7.66 0.58 9.84 5.47 3.54 65.13 12.15 0.46 13.25 3.99 3.21 76.13 8.51 0.4 7.77Stdev 4.13 4.95 25.22 6.93 0.46 16.36 2.34 3.17 28.47 15.01 0.38 18.58 2.76 4.39 21 6.31 0.47 12.72Cross      Mean 12.88 9.42 38.56 9.96 0.9 28.28 6.33 6.61 30.02 19.78 0.63 36.62 4.2 7.87 54.32 11.09 0.87 21.64Stdev 2.85 7.46 14.79 5.98 0.57 17.86 3.38 2.17 13.51 19.56 0.44 15.37 1.92 7.85 24.56 4.79 0.79 14.18Single      Mean 6.07 2.81 77.49 7.18 0.51 5.95 5.29 2.9 72.52 10.54 0.42 8.33 3.94 2.2 80.84 7.95 0.3 4.77Stdev 3.3 3.37 21.49 7.09 0.41 13.28 2.07 2.97 25.07 13.65 0.36 15.24 2.93 2.39 17.12 6.52 0.29 10.33

Panel C: Average Trade SizeAll      Mean 2,086 3,379 946 2,230 1,520 2,577 2,298 2,668 1,152 4,624 1,777 2,859 2,728 3,299 1,617 2,904 2,685 2,803Stdev 1,752 7,229 675 1,865 1,069 2,748 1,870 1,998 1,068 9,003 1,656 3,814 2,812 3,011 1,644 3,220 3,571 2,634Cross      Mean 2,794 8,289 784 1,985 1,574 3,335 2,354 3,039 946 9,241 2,014 5,317 2,569 3,203 1,304 2,296 2,542 2,858Stdev 1,648 16,660 477 1,626 1,109 2,768 1,525 1,357 600 16,611 1,130 7,822 1,556 1,185 818 1,436 1,212 1,179Single      Mean 1,937 2,345 980 2,282 1,509 2,418 2,286 2,587 1,196 3,652 1,732 2,341 2,763 3,317 1,684 3,036 2,713 2,793Stdev 1,758 2,176 711 1,927 1,075 2,754 1,952 2,118 1,143 6,387 1,747 2,130 3,031 3,261 1,773 3,489 3,879 2,838

33

34

Table 13 Buy Ratio by Nationality

  2004 2005 2006 2007 2008 2009  A D F A D F A D F A D F A D F A D FPanel A-Buy RatioAll

Mean100.

0099.98

100.09

100.00

99.92

100.04

99.97

99.91

99.99

99.97

99.94

99.99

99.95

99.90

100.01

99.88

99.91

100.02

DifferenceLevel

t-stat

Level

t-stat

Level

t-stat

Level

t-stat

Level

t-stat

Level

Domestic-Arab

-0.02

-0.6

8-

0.08

-4.6

5-

0.06

-3.6

7

-0.0

3

-2.9

7

-0.0

5

-3.7

60.0

33.0

1

Domestic-Foreign

-0.11

-3.0

2-

0.12

-5.8

0-

0.08

-3.8

2

-0.0

5

-3.5

4

-0.1

1

-6.2

1

-0.1

1

-6.9

9

Arab-Foreign-

0.09

-1.8

4-

0.04

-1.7

1-

0.02

-0.7

7

-0.0

2

-0.9

8

-0.0

6

-2.8

8

-0.1

4

-8.0

8Cross

Mean100.

0799.97

100.12

100.02

99.92

100.02

100.00

99.94

99.99

99.97

99.94

99.98

99.92

99.86

100.02

99.92

99.93

100.06

DifferenceLevel

t-stat

Level

t-stat

Level

t-stat

Level

t-stat

Level

t-stat

Level

Domestic-Arab

-0.10

-1.4

3-

0.10

-4.0

1-

0.06

-1.6

9

-0.0

3

-2.6

4

-0.0

6

-2.6

90.0

10.3

2

Domestic-Foreign

-0.15

-2.3

3-

0.10

-3.9

7-

0.05

-1.5

5

-0.0

4

-2.9

4

-0.1

5

-6.3

3

-0.1

3

-6.5

3

Arab-Foreign-

0.06

-0.6

4 0.000.0

1 0.010.2

1

-0.0

1

-0.5

2

-0.0

9

-3.3

0

-0.1

3

-5.6

3Single

Mean99.9

499.98

100.04

99.99

99.93

100.06

99.95

99.90

99.98

99.97

99.94

99.99

99.96

99.90

100.01

99.87

99.91

100.00

DifferenceLevel

t-stat

Level

t-stat

Level

t-stat

Level

t-stat

Level

Level

Domestic-Arab 0.04

1.69

-0.07

-3.0

4-

0.06

-3.0

1

-0.0

3

-2.4

0

-0.0

5

-3.1

20.0

43.1

7Domestic-Foreign

-0.06

-2.0

-0.13

-4.3

-0.09

-3.0

-0.0

-2.8

-0.1

-4.3

-0.0

-4.4

35

4 8 0 5 3 0 6 9 5

Arab-Foreign-

0.10

-2.7

3  -

0.07

-2.0

1  -

0.03

-0.9

3  

-0.0

2

-0.8

9  

-0.0

5

-1.8

7  

-0.1

4

-5.8

3  

36

Table 14 Sell Ratio by Nationality

  2004 2005 2006 2007 2008 2009  A D F A D F A D F A D F A D F A D FPanel B-Sale RatioAll

Mean100.1

5100.0

9100.0

3100.1

3100.0

9100.0

4100.0

8100.1

2100.0

6100.0

8100.0

8100.0

4100.1

1100.1

1 99.99100.1

2100.0

7100.0

4Difference Level Level Level Level Level LevelDomestic-Arab -0.06 -1.88 -0.04 -2.28 0.05 2.95 0.00 0.05 0.00 -0.19 -0.05 -3.36Domestic-Foreign 0.06 2.96 0.05 2.22 0.07 2.85 0.04 3.14 0.11 6.02 0.03 2.14Arab-Foreign 0.12 3.59 0.08 3.42 0.02 0.76 0.04 2.69 0.12 5.40 0.08 4.14

Cross

Mean100.1

2100.1

5100.0

3100.0

9100.0

9100.0

3100.1

0100.1

2100.1

1100.0

5100.0

7100.0

3100.1

3100.1

1100.0

0100.1

1100.0

4100.0

0Difference Level Level Level Level Level LevelDomestic-Arab 0.02 0.34 0.01 0.34 0.02 0.57 0.02 1.40 -0.03 -1.03 -0.07 -1.48Domestic-Foreign 0.12 2.72 0.06 2.20 0.01 0.25 0.04 2.76 0.11 4.00 0.05 2.16Arab-Foreign 0.10 1.69 0.05 1.57 -0.01 -0.19 0.02 1.38 0.14 4.22 0.12 2.31

Single

Mean100.1

7100.0

7100.0

3100.1

5100.0

9100.0

5100.0

7100.1

2100.0

2100.0

9100.0

8100.0

4100.1

0100.1

1 99.99100.1

3100.0

8100.0

6Difference Level Level Level Level Level LevelDomestic-Arab -0.10 -4.04 -0.06 -2.90 0.06 3.19 -0.01 -0.42 0.00 0.22 -0.05 -3.43Domestic-Foreign 0.04 1.27 0.04 1.25 0.11 3.68 0.04 2.26 0.11 4.83 0.02 0.83Arab-Foreign 0.14 3.61   0.10 2.81   0.05 1.54   0.05 2.25   0.11 4.13   0.06 2.72  

37

Table 15 Buy Ratio by Nationality and Type 2004-2006

  2004 2005 2006

  A-Ind A-Inst D-IndD-Inst F-Ind F-Inst A-Ind A-Inst D-Ind

D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind

D-Inst F-Ind F-Inst

Panel A: Buy Ratio      All      Mean 99.99 100.02 99.98 99.96 100.07 100.1 99.98 100.05 99.97 99.82 99.95 100.11 99.94 100.03 99.97 99.79 99.89 100.06  Diff t-stat      Ainst-Aind 0.03 0.28   0.06 1.91   0.09 2.66  Dinst-Dind -0.03 -1.39   -0.15 -6.21   -0.18 -9.48  Finst-Find 0.03 0.44   0.16 4.26   0.17 4.27  Dinst-Ainst -0.06 -0.64   -0.22 -6.12   -0.24 -7.03  Dinst-Finst -0.14 -2.56   -0.29 -9.35   -0.28 -10.11  Dind-Arabind -0.01 -0.26   -0.01 -0.8   0.03 1.67  Dind-Find -0.09 -2.39   0.02 0.6   0.08 2.18  Cross      Mean 100.07 100.06 100.02 99.91 100.11 100.13 100.03 100.01 99.95 99.87 99.98 100.04 99.98 100.02 99.97 99.89 99.88 100.06  Diff t-stat      Ainst-Aind -0.01 -0.05   -0.02 -0.35   0.04 0.66  Dinst-Dind -0.11 -2.19   -0.08 -2.54   -0.08 -1.9  Finst-Find 0.02 0.2   0.06 1.21   0.18 2.87  Dinst-Ainst -0.15 -1.04   -0.14 -3.01   -0.13 -2.12  Dinst-Finst -0.22 -2.47   -0.17 -5.21   -0.17 -3.79  Dind-Arabind -0.05 -0.62   -0.07 -2.47   -0.01 -0.14  Dind-Find -0.09 -1.4   -0.03 -0.65   0.09 1.5  Single      Mean 99.94 99.96 99.97 99.99 100.02 100.06 99.97 100.08 99.97 99.8 99.93 100.18 99.92 100.03 99.97 99.74 99.9 100.07  Diff t-stat      Ainst-Aind 0.02 0.28   0.12 2.4   0.11 2.78  Dinst-Dind 0.02 0.88   -0.18 -5.47   -0.23 -10.37  Finst-Find 0.03 0.52   0.26 4.47   0.17 3.18  Dinst-Ainst 0.04 0.57   -0.28 -5.29   -0.29 -7.21  Dinst-Finst -0.06 -1.43   -0.39 -7.81   -0.33 -8.78  Dind-Arabind 0.03 1.55   0.01 0.35   0.04 2.23  Dind-Find -0.05 -0.94   0.05 1.1   0.07 1.57  

38

39

Table 16 Buy Ratio by Nationality and Type 2007-2009  2007 2008 2009  A-Ind A-Inst D-Ind D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind D-Inst F-Ind F-InstPanel A: Buy Ratio              All      Mean 99.97 99.96 99.97 99.88 99.95 100.01 99.97 99.9 99.93 99.86 99.9 100.1 99.94 99.78 99.97 99.84 99.94 100.09       Ainst-Aind -0.01 -0.48   -0.07 -2.62   -0.16 -7.56Dinst-Dind -0.1 -7.81   -0.07 -4.45   -0.13 -10.82Finst-Find 0.06 2.28   0.2 5.86   0.14 4.66Dinst-Ainst -0.09 -4.44   -0.05 -1.82   0.06 2.87Dinst-Finst -0.13 -7.84   -0.24 -10.08   -0.25 -12.63Dind-Arabind 0 0.09   -0.05 -3.01   0.03 2.81Dind-Find 0.02 0.94   0.03 0.98   0.03 0.98Cross      Mean 99.96 99.99 99.95 99.92 99.94 100 99.92 99.93 99.86 99.87 99.84 100.11 99.91 99.93 99.94 99.91 99.98 100.1       Ainst-Aind 0.03 1.49   0.01 0.26   0.02 0.56Dinst-Dind -0.03 -2.47   0.01 0.19   -0.03 -1.67Finst-Find 0.07 2.26   0.27 5.42   0.12 2.96Dinst-Ainst -0.07 -3.32   -0.06 -1.83   -0.02 -0.66Dinst-Finst -0.08 -4.73   -0.24 -7.93   -0.19 -7.75Dind-Arabind 0 -0.24   -0.06 -1.99   0.03 1.32Dind-Find 0.02 0.7   0.02 0.42   -0.04 -1Single      Mean 99.98 99.95 99.98 99.87 99.96 100.02 99.99 99.89 99.94 99.85 99.91 100.09 99.94 99.71 99.98 99.82 99.93 100.08       Ainst-Aind -0.02 -0.94   -0.09 -2.71   -0.23 -8.64Dinst-Dind -0.11 -7.37   -0.09 -4.63   -0.16 -10.71Finst-Find 0.06 1.8   0.18 4.09   0.14 3.59Dinst-Ainst -0.09 -3.37   -0.04 -1.2   0.1 3.85Dinst-Finst -0.15 -6.51   -0.24 -7.42   -0.26 -9.5Dind-Arabind 0 0.1   -0.05 -2.55   0.03 2.45Dind-Find 0.02 0.73   0.03 0.73   0.04 1.36

40

Table 17 Sell Ratio by Nationality and Type 2004-2006

  2004 2005 2006  A-Ind A-Inst D-Ind D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind D-Inst F-Ind F-InstPanel B: Sell Ratio    All    

Mean 100.15 100.14 100.02100.2

7 100.08 100 100.15 100.06 100.04 100.2 100.09 100.01 100.08 100.07 100.04100.2

8 100.08 100.04  Diff t-stat    Ainst-Aind -0.01 -0.17   -0.1 -2.85   -0.02 -0.49Dinst-Dind 0.25 7.74   0.16 9.32   0.25 13.99Finst-Find -0.08 -1.99   -0.07 -1.87   -0.04 -0.93Dinst-Ainst 0.12 2.75   0.14 4.29   0.22 7.04Dinst-Finst 0.27 7.57   0.19 6.69   0.25 8.05Dind-Arabind -0.13 -3.55   -0.12 -6.38   -0.04 -2.55Dind-Find -0.06 -1.61   -0.05 -1.46   -0.04 -1.13Cross    

Mean 100.13 100.12 100.07100.2

5 100.04 100.02 100.08 100.1 100.06100.1

4 100.07 100.01 100.09 100.1 100.04 100.2 100.19 100.05  Diff t-stat    Ainst-Aind -0.01 -0.12   0.02 0.47   0.01 0.09Dinst-Dind 0.18 2.23   0.08 3.24   0.15 4.21Finst-Find -0.03 -0.53   -0.06 -1.21   -0.14 -1.76Dinst-Ainst 0.13 1.66   0.04 0.87   0.1 1.95Dinst-Finst 0.23 3.35   0.13 3.84   0.14 3.16Dind-Arabind -0.06 -0.68   -0.02 -0.63   -0.05 -1.21Dind-Find 0.02 0.39   -0.01 -0.29   -0.15 -2Single    

Mean 100.17 100.17 100.01100.2

8 100.12 99.97 100.18 100.02 100.03100.2

3 100.09 100.01 100.08 100.04 100.03100.3

2 100.01 100.02  Diff t-stat    Ainst-Aind 0.01 0.09   -0.17 -3.68   -0.03 -0.92Dinst-Dind 0.27 12.16   0.19 8.59   0.28 13.35Finst-Find -0.14 -2.18   -0.08 -1.39   0.01 0.11Dinst-Ainst 0.1 1.86   0.21 4.64   0.28 7.13Dinst-Finst 0.3 7.56   0.21 5.12   0.3 7.3Dind-Arabind -0.16 -5.92   -0.15 -6.79   -0.04 -2.14Dind-Find -0.11 -1.95   -0.06 -1.31   0.02 0.47

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Table 18 Sell Ratio by Nationality and Type 2007-2009

  2007 2008 2009

  A-Ind A-Inst D-Ind D-Inst F-Ind F-Inst A-Ind A-Inst D-Ind D-Inst F-IndF-Inst A-Ind A-Inst D-Ind D-Inst F-Ind

F-Inst

Panel B: Sell Ratio    All    Mean 100.08 100.08 100.03 100.18 100.04 100.04 100.12 100.08 100.07 100.17 100.08 99.93 100.11 100.15 100.03 100.13 100.13 99.96     Ainst-Aind 0 0   -0.04 -1.44   0.05 1.75Dinst-Dind 0.15 11.63   0.1 6.13   0.1 7.69Finst-Find 0 -0.05   -0.15 -4.02   -0.17 -5.54Dinst-Ainst 0.1 4.73   0.08 3.08   -0.02 -1.14Dinst-Finst 0.14 7.5   0.24 9.49   0.17 8.09Dind-Arabind -0.06 -4.35   -0.06 -3.46   -0.08 -3.83Dind-Find -0.01 -0.59   -0.01 -0.42   -0.1 -3.83Cross    Mean 100.04 100.06 100.05 100.1 100.06 100.01 100.18 100.08 100.09 100.12 100.15 99.93 100.15 100.07 100.03 100.05 100.12 99.93     Ainst-Aind 0.02 0.87   -0.1 -2.49   -0.08 -0.95Dinst-Dind 0.05 3.04   0.03 1.16   0.02 1.01Finst-Find -0.05 -1.8   -0.22 -3.51   -0.19 -4.35Dinst-Ainst 0.03 1.37   0.05 1.29   -0.01 -0.49Dinst-Finst 0.09 4.66   0.2 6.16   0.12 4.92Dind-Arabind 0.01 0.37   -0.09 -2.65   -0.12 -1.41Dind-Find -0.01 -0.46   -0.05 -0.9   -0.08 -2.05Single    Mean 100.09 100.09 100.02 100.2 100.03 100.05 100.11 100.09 100.06 100.18 100.06 99.93 100.1 100.19 100.03 100.15 100.13 99.98     Ainst-Aind 0 -0.03   -0.02 -0.66   0.09 3.36Dinst-Dind 0.18 11.17   0.12 6.01   0.12 7.78Finst-Find 0.02 0.67   -0.13 -2.82   -0.15 -3.68Dinst-Ainst 0.11 4.11   0.09 2.66   -0.04 -1.44Dinst-Finst 0.15 5.67   0.24 7.52   0.16 5.56Dind-Arabind -0.07 -4.49   -0.05 -2.64   -0.07 -4.56Dind-Find -0.01 -0.38   0 -0.02   -0.1 -3.23

42