Price Linkages and Integration

Of The Cairo Stock Exchange

Sam R. Hakim, Ph.D.*

Abstract

This paper analyzes the growth, performance, and properties of the Cairo StockExchange (CSE) between 1995 and 2000. An integral part of the MENA (MiddleEast and North Africa) region, the CSE along with Amman, Istanbul, andCasablanca are often regarded as a group apart from other emerging orinternational markets. They serve as good examples of newly emerging capitalmarkets with significant growth potential. Results of previous studies suggestthat these stock markets have 3 main characteristics: (a) are sensitive to thecountry's political changes, (b) have considerable growth potential, but (c) needto develop structural relations with major foreign markets and regional stockexchanges. Our results indicate that prices on the CSE follow a random walk, animportant characteristic of efficient markets. Relying on causality andcointegration analysis, we show that Cairo has short-term links with Amman,Istanbul, Tel Aviv and the US. We are also able to identify a weak but uniqueand stable long-term relation between Egyptian and US stock. While embryonic,the relation suggests that the CSE may be beginning to integrate with thedominant US market. Meanwhile, the lack of integration between CSE and itsregional counterparts, namely Tel Aviv and Amman, suggests that the peacedividend has failed to materialize in the financial sector and that the three stockmarkets remain segmented from one another. As such, Cairo offers foreigninvestors risk and return profiles that are unique in the region and diversificationbenefits unavailable elsewhere in MENA.

* Vice President, Energetix Corp., Houston, Texas. Email: hakimsam@yahoo.com

2

1. INTRODUCTION

Recently, there has been a shift in attention to the emerging markets of

developing countries (Bekaert and Harvey 1997, DeSantis and Imrohoroglu 1997).

This focus stems from the belief that these markets present portfolio and fund

managers a new possibility to enhance and optimize their portfolios. For example,

Harvey (1993), and Ferson and Harvey (1993) found that stock market returns in

emerging markets were high and predictable but lacked strong correlation with

major markets. As emerging markets mature, they are likely to become

increasingly sensitive to the volatility of stock markets elsewhere. Their

increasing degree of integration with world markets will diminish their ability to

enhance and diversify international portfolios.

This paper analyzes the performance, properties and links of the CSE

during the past 5 years. A prominent equity market in the Middle East and North

Africa (MENA) region, the CSE serves as a good example of a newly emerging

capital market with significant growth potential. Results of previous studies

(Azzam 1997, Darrat & Hakim 1997, El Erian 1995) suggest that the MENA stock

markets have 3 main characteristics: (a) are sensitive to the country's political

changes, (b) have considerable growth potential, but (c) need to develop structural

relations with major foreign markets and regional stock exchanges. As such, they

have the potential of offering unique risk-return characteristics to investors

seeking international diversification. A case in point was the Asian crisis in the

fall of 1997. While many emerging markets suffered backlashes from South East

Asia, the MENA countries were among the few where the repercussion effects

were minimal.

This paper complements the existing literature on the MENA region by

analyzing the interdependence of the CSE and integration with the world stock

markets. As the CSE matures, it becomes increasingly important to understand its

properties and links with equity markets in the region and elsewhere.

3

In the MENA region, four stock markets stand out. They are Amman,

Casablanca, Istanbul, and Tel Aviv. As far as mature stock markets are

concerned, we will examine the links between CSE and London, Paris, and New

York. To the extent that CSE is emerging, we will examine the extent to which it

is integrated with other emerging markets using an index of emerging stock

markets in the world.

Our objective is to investigate the salient price linkages between the CSE

and the fledgling stock markets in MENA, Europe and the US. Part 2 gives a

brief introduction of the salient features of the CSE. In part 3, we analyze the data

and review the descriptive statistics of the CSE. Part 4 focuses on market

efficiency by testing whether CSE prices follow a random walk. Part 5 analyzes

the return linkages between CSE and MENA and non-MENA stock markets using

Granger-causality techniques. Part 6 tests for the existence of a long-term stable

relation between CSE and each of the stock markets we analyze. The long- and

short-term dynamics are investigated in part 7. Part 8 summarizes and concludes

the paper.

2. The CSE: A BRIEF BACKGROUND

Egypt's Stock Exchange is comprised of two exchanges, Cairo and

Alexandria, both of which are governed by the same board of directors and share

the same trading, clearing and settlement systems. The Alexandria Stock

Exchange was officially established in 1888, with Cairo following in 1903. Both

exchanges were very active in the 1940's, and the combined Egyptian Stock

Exchange ranked fifth in the world. The central planning and socialist policies

adopted in the mid 1950's led to the Stock Exchange's dormancy between 1961

and 1992. In the 1990's, the Egyptian government's restructuring and economic

reform program resulted in the revival of the Egyptian stock market, and a major

change in the organization of the Cairo and Alexandria Stock Exchanges took

4

place in January 1997 with the election of a new board of directors and the

establishment of a number of board committees.

The stock market has expanded fast since it was revived by the 1992

Capital Market Law. Privatization through the stock market has been successful

since 1996, when the government decided to give up control of selected

companies by floating majority stakes. About half of all privatization transactions

have taken place through public offerings on the stock market. Moving ahead, the

main elements of future programs entail an effort to streamline capital market

institutions and a significant growth in the number of government institutions

earmarked for sale.

So far this year, the performance of MENA stock markets have not been

impressive. As the following table reveals, MENA has ranked behind many

emerging regions. The Egyptian equities also had a lackluster performance

ranking 9 among 11 Middle Eastern and African countries.

With the possible exception of Istanbul, Tel Aviv, and Amman, MENA

equity markets have only come to the fore in the 1990s. Istanbul is now the

6

region’s dominant financial market. At over $62 billion in capitalization, 270

active listed companies, and a daily trading volume of $1.25 billion, its growth is

driven primarily by domestic rather than foreign investors. Among other MENA

stock markets, Istanbul has the highest foreign participation. Even there, foreign

funds account for less than 20% of the market volume. The limited share of

foreign participation has been a boon for the MENA stock markets during the

crisis of South East Asia in October 1997. The small reliance on foreign funds

helped insulate MENA markets from the severe repercussions felt in other

emerging markets more dependent on foreign capital. Comparison between CSE

and other stock markets in MENA is provided in the following tables.

7

While a market capitalization steadily increasing since 1992, CSE remains

half of that of Istanbul. At $31 billion, it is six times bigger than Amman which

effectively has been treading water during the past 5 years. The number of listed

companies is over 1000, but this figure is misleading because a large number of

securities do not trade. A better measure is the number of active companies.

Here, the comparison with Istanbul is similar to the market capitalization. With a

market capitalization relative to GDP amounting to 30%, CSE is also similar to

Istanbul. Only Amman is considerably higher with a figure close to 50%. As of

May 2000, the average P/E on the CSE has hovered around 7 with a dividend yield

of approximately 13%. Meanwhile, liquidity remains a problem but is not limited

to one specific sector. The tables below show the top 10 companies actively listed

on the CSE in terms of P/E and liquidity.

Liquidity of the 10 Most Active in Terms of Volume Traded

Name of Company Market CapLE MM

Avg Daily Vol.in ‘000

Egyptian Media Production City 8519 1238Mobinil 13100 406El Rasheed 32 1778Commercial Int’l Bank (CIB) 2429 188AIC 250 164Al Kahera Housing 47 109Lakah Group 1261 656th of October 104 61Misr Chemical 140 58Suez Cement 2226 56

Cognizant of its current limitations, and realizing that the stock exchanges

will require some form of integration to enhance efficiency, liquidity and remain

competitive, the CSE has embarked on a project to explore avenues for

cooperation with financial institutions throughout the MENA region and Africa.

8

3. DATA AND DESCRIPTIVE STATISTICS

Capital markets in the Gulf states have traditionally been less important in

channeling financial funds. For example, compared with its MENA counterparts,

the Saudi stock market grew only by 10% since 1993.

Characteristics of MENA Stock MarketsStock

ExchangeDate of

OperationListedCos.

Capitalization(billions US$)

1993 1997

Capitalization/GDP Ratio (%)1993 1997

TurnoverRatio (%)

1997**Amman 1978 114 3.36 5.46 89.8 78 14.5Bahrain 1957 40 5.64 7.83 110.2 142.4 9.36Cairo 1992 646 5.28 20.88 11.3 28.9 28Casa 1929 49 2.7 12.25 10.5 30.6 8.7Istanbul 1986 258 37.82 61.88 91.79 126.3 93.6Kuwait 1952 66 11.32* 27.24 43.6 77.9 127Saudi 1935 70 53 59.4 44 42.8 27.8New York 1865 3694 4826 9522 76.1 134 61Sources: Arab Monetary Fund, Quarterly Bulletins, First Quarter 1998.Reuters Business Briefing.International Financial Statistics, Various issues.*1994.

**Turnover ratio: Total trading/Average capitalization

9

In contrast, Cairo and Casablanca grew four folds over the same time

period. This spectacular growth is attributed to a series of market reforms and a

massive privatization program these countries have launched.

Our data consists of weekly closing price series for each stock market

obtained from Morgan Stanley equity indices. Compounded week-to-week returns

are calculated as the natural log differences in prices: log (Pt/Pt-1).

Weekly Return Comparison with other stock markets (in US$)May 1995 – May 2000

Cairo Casa Amman Istanbul Tel Aviv Emerg Mkts London NY Mean 0.30% 0.20% -0.15% 0.37% 0.28% 0.04% 0.24% 0.42% Median 0.02% 0.16% -0.34% 0.38% 0.59% 0.31% 0.29% 0.59% Maximum 11.78% 6.29% 6.90% 19.39% 7.68% 6.72% 5.67% 6.43% Minimum -7.58% -6.17% -3.73% -20.68% -12.43% -12.93% -4.42% -8.53% Std. Dev. 2.75% 1.51% 1.70% 6.08% 2.92% 2.45% 1.66% 1.81% Skewness 1.01 0.28 0.89 -0.08 -0.70 -1.00 -0.13 -0.58 Kurtosis 5.63 5.17 4.84 3.66 4.95 6.72 3.22 5.20Sharp Ratio 11% 14% -9% 6% 10% 2% 15% 23% Jarque-Bera 119.49 54.65 71.70 5.06 62.53 194.17 1.20 67.36 Probability 0 0 0 0.0797 0 0 0.5489 0

We begin by examining the statistical properties of the CSE by a plot of its

histogram. We also compare the weekly performance of the CSE with other

equity market between May 95 and May 2000. With an average weekly return of

0.30%, we find CSE’s significantly higher than the emerging market index and

second only to Istanbul in the MENA region. This represents an average over 5

years and corresponds to 15% in annual terms1. For an investor, what matters of

course is the return per unit of risk, a measure similar to a Sharp Ratio. Using this

measure, we find that the CSE to be second only to Casa but with considerable

more liquidity. This should provide a degree of comfort to foreign investors

seeking higher risk-adjusted returns with a sufficient market capitalization and

liquidity.

1 The returns weekly mean and standard deviation are annualized by multiplying each with 52 and square root of 52respectively.

10

Comparing the distribution of the CSE with other stock markets, we find

that most stock markets have skewed returns with significant variability in

kurtosis. The skewness (S) and kurtosis (K) are computed as follows:

3

3

1)(

σNRR

SN

i i∑ =−

=

and

4

4

1)(

σNRR

KN

i i∑ =−

=

where RRi , represent the return in week i and the average return for the series

respectively. For a normal distribution, S and K are respectively 0 and 3.

Clearly, most markets exhibit substantial departures from normality. We formally

tested for normality of the return distributions using the Jarque Bera Statistic (JB).

Under the null hypothesis of normality, JB is distributed χ2 with 2 degrees of

freedom. JB is defined as:

−+= 22 )3(

41

6KSTJB

11

where S and K represent the Skewness and Kurtosis. The null hypothesis of

normal returns is rejected for all stock markets with the exception of London.

The bias in CSE distribution is evident in the figure below.

Cairo Stock ExchangeDistribution of Returns

0

10

20

30

40

-0.05 0.00 0.05 0.10

Cairo Stock Market Returns May 1995 - May 2000

Mean 0.002957Median 0.000219Maximum 0.117790Minimum -0.075846Std. Dev. 0.027519Skewness 1.011701Kurtosis 5.625520

Jarque-Bera 119.4892Probability 0.000000

We shed more light on the statistical properties of the stock market prices

on the CSE by examining their autocorrelation function. We compute the

correlation coefficient of values t periods apart as:

21

1

)(

))((

PP

PPPPT

i t

titT

i tt ∑

∑=

+−

=

−

−−=ρ

where the P’s represent the level of the stock market index (or price). When ρρρρt is

large, the prices are serially correlated. If the correlations fall precipitously as the

number of lags increases then stock market prices exhibit a low order

autoregressive process.

12

Correlation Analysis of Weekly Priceson the Cairo Stock Exchange

May 1995 –May 2000Weekly lags AUTOCORREL. PART. AUTO. Q-Stat*

1 0.987 0.987 258.112 0.97 -0.155 508.373 0.951 -0.056 749.994 0.929 -0.133 981.35 0.905 -0.047 1201.66 0.88 -0.006 1410.97 0.854 -0.046 1608.88 0.826 -0.089 1794.49 0.798 0.046 1968.6

10 0.769 -0.054 2131.1 * All sSignificant at 5%

From the table above, we find that this is not the case for the CSE prices. In

the same table, we also provide the partial autocorrelation coefficient (PAC) which

stems from a regression of a price series Xt on its lags Xt-1, …, Xt-n. The PACs are

large and do not die off quickly even after many lags. To test the hypothesis that

all the autocorrelations are zero (i.e. ρ1 = ρ2 … = ρn = 0), we computed the Ljung-

Box Q-statistic defined as:

Q N NN i

i

i

p

= +−=

∑( )22

1

ρ

Q is distributed χ 2 with degrees of freedom equal to the order of the PAC

coefficients, p. We find that the Q statistics are highly significant. Overall these

statistics suggest the price moves are dependent. The large autocorrelations

indicate that following a shock, CSE prices have little tendency to return to their

usual level. To the contrary, a random disturbance in either direction will affect

prices for several weeks.

If the sum of ρ1 and ρ2 add to unity, the series is said to have a unit root.

This implies that the series in question is non-stationary with a non-defined mean,

variance or higher moments. Typically, most time series have this characteristic.

If anything, unit roots is a sign that stock prices are unpredictable and the market

is efficient.

13

4. TESTS OF UNIT ROOTS IN STOCK PRICES

We begin by examining the stochastic nature of the stock price series on the

CSE. We show that stock price series derive from a unit root process which can

be written as:

y t y ut t t= + + +−β β α0 1 1

where β0 is a drift parameter and t is a time trend. The process can be rewritten in

first-difference form as:

∆y t y ut t t= + + − +−β β α0 1 11( )

The test for unit root is essentially to test if ∀ =1.

We report the results from the unit root test in the table below.

Weekly Prices of CSEMay 95-2000

Unit Root Test Statistics

10% Critical Value 5% Critical Value Phillips PerronPrice Levels -2.573 -2.873 -0.9871st Differences -2.573 -2.873 -12.237

The results clearly reject the null hypothesis of unit root in the differences but not

in the levels. From these results, we conclude that Cairo stock prices are ~I(1).

This is not surprising since earlier results from Darrat & Hakim (1997) indicated

that MENA stock prices were generally stationary even though their sample period

was relatively short.

Our next step is to estimate the linkages between CSE and other stock

markets. Granger causality tests are used to determine the direction of causality

between each pair. Our analysis is based on the individual market returns rather

14

than levels because the inferences based on the standard regression model do not

hold when the regressors are non-stationary.

5. CAUSAL RELATIONSHIPS BETWEEN CSE AND OTHER STOCK

MARKETS

This section performs Granger Causality tests to examine the relationship

between equity returns on the CSE and stock markets in MENA and non-MENA

regions. Weekly data of stock returns are used to investigate the effects of

unidirectional and bi-directional causality. We pair CSE with the 4 other

emerging stock markets in MENA, the emerging market comprehensive equity

index, and the stock market indices of London and New York.

The causality tests are conducted for 3 lags. Formally, let Y and X represent

two series, Granger causality addresses the question whether X is linearly

informative about a future Y. This would hold true only when the event X

precedes the event Y. Stated differently, this presumes that the current and past

observations of X help in the forecast of Y. To conduct the test, each series is

regressed on its lag and those of other variables. To examine the endogeneity of

an individual market, we run least squares on the following models for each pair

of stock markets:

tjtj ji itit

tjtj jiti it

XYX

YXY

υαα

ναα

++=

++=

−== −

−=−=

∑∑∑∑

2

1

2

0

2

1

2

0

where Xt and Yt are the weekly returns for the CSE and each of the other stock

markets respectively. The estimated parameters β’s capture the impact of the

exogenous variable (the independent variable) on the endogenous variable (the

dependent variable). The causality tests consists of an F test for the null

hypothesis:

H0: β1 = β2 = 0

15

For the first equation in the model above, the null hypothesis is X does not

Granger cause Y.

Table 5Return Linkages Between CSE and other stock markets

Mar 95-2000

Null HypothesisCSE has no impact on XX has no impact on CSE

F-Stat p-value

MENA Stock MarketsCSE --/--> AMMAN 2.22942 0.08528AMMAN --/--> CSE 0.8402 0.47294

CSE --/--> CASA 0.72931 0.53535CASA --/--> CSE 0.60499 0.61232

ISTANBUL --/--> CSE 2.82423 0.03932CSE --/--> ISTANBUL 3.00466 0.03102

CSE --/--> Tel Aviv 0.31898 0.81165CAIRO --/--> Tel Aviv 3.0812 0.02805

Non – MENA Stock Markets

Emerg Mkt index --/--> CSE 1.88632 0.13236CSE --/--> Emerg Mkt Index 0.60201 0.61425

NY --/--> CSE 2.84833 0.03809CSE --/--> NY 1.23913 0.29604

The results are summarized in the table above, where it appears that CSE

has strong links with both MENA and non-MENA equity markets. Specifically,

CSE seems to impact Amman but not the other way around. Similarly, Tel Aviv

has a one way impact on CSE. We suspect that Tel Aviv influences Cairo

indirectly because of the links the Tel Aviv stock exchange enjoys with the US

market. Istanbul and Cairo however enjoy a two-way causality, a result expected

given the prominence and the size of these 2 markets in MENA. Casablanca, on

the other hand, seems to have no causal link with Cairo. We suspect that Morocco

has recently emerged among the stock markets of Africa and that its links with

16

Cairo may strengthen over time. With regards to the non-MENA countries, the

CSE shows a weak impact from the emerging markets index worldwide, possibly

a reflection of the fact that foreign investors do not yet regard the CSE as a

prominent member among more established emerging markets elsewhere, like

South East Asia or Latin America for example. Perhaps more important is the

strong impact that the US stock market exerts on the CSE. In the next section, we

will explore this link in more detail using cointegration analysis in an effort to

investigate the existence of stable long-term relationship between the CSE and

each stock market. A graphical depitction of possible co-movements between

CSE and the emerging market index on the other is shown in the graph below.

For comparison purposes, we also conducted causality tests between

Istanbul and the US and also Tel Aviv and the US. The results (available from the

author on request) show that a one-way causality between the US and each of the

17

equity markets. It is important to note that other established emerging markets in

South East Asia and Latin America also exhibit similar one-way links to the US

market.

In summary, the results reveal that the CSE occupies an important role

among the MENA stock markets with a strong short-term link with the US, in

concert with other emerging markets in MENA and elsewhere.

6. INTEGRATION OF THE CSE: A COINTEGRATION ANALYSIS

In this section, we explore the price linkage between CSE and other stock

markets by relying on cointegration analysis discussed in Engle and Granger

(1987) and the test procedures developed in Johansen and Juselius (1992).

Briefly, cointegration analysis suggests that two (or more) variables which

are individually non-stationary may become stationary in a linear combination.

Specifically, if two variables X ~ I(1) and Y ~ I(1) but their linear combination X-

ϕY ~ I(0), then they are cointegrated, with ϕ representing their cointegrating

relationship. Naturally ϕ may not be unique in a multivariate setting. Johansen

(1988) and Johansen and Juselius (1992) provide appropriate maximum likelihood

techniques for investigating cointegration in time series models. The cointegration

analysis will help us determine the degree to which the CSE is integrated with

other equity markets, in particular, the U.S. stock market. A finding of no

cointegrating relationship with the U.S. market would suggest that the CSE is

segmented internationally and therefore its performance can diverge significantly

and permanently from the U.S. market. This result would warrant a risk premium

on its stocks to the extent that international investors stand to benefit from the

added risk diversification the CSE provides. On the other hand, the presence of a

cointegrating relationship between CSE and other MENA equity markets suggests

that the CSE and its counterpart are regionally linked by a long-term (equilibrium)

relationship. Although one market may drift away temporarily in the short term,

18

economic and financial forces will ensure that its returns will revert back to the

long-term link with its regional counterpart.

We investigate the cointegrating relations with the CSE in a sequence of

bivariate models using Johansen's full information maximum likelihood

procedure. The systems we examine are: {CSE, London}, {CSE, Paris}, {CSE,

Other Emerg Mkts}, {CSE, Amman}, {CSE, Casa}, {CSE, Istanbul}, {CSE, Tel

Aviv}, {CSE, US}.

Given the results of the unit root tests of the preceding section, the

cointegration analysis are performed on the levels of stock prices to ensure that the

variables tested for cointegration enter the tests in their non-stationary forms.

The results are reported in the nearby where for ease of exposition we only

report the results based on 8 lags but with different trend in the data or the VAR.

Other lag structures were tried and gave similar results. The findings reveal a lack

of any stable and long-term relationship between CSE and each of the other stock

market in MENA or elsewhere. A potential exception is a unique link with the US

equity market. Although the relationship is statistically significant (at 5%), it is

also sensitive to the number of lags selected leading one to conclude that the

relation may be weak and embryonic.

The finding of a single and significant cointegrating vector with the US

contrasts with earlier results by Darrat and Hakim (1997) who concluded that that

the Egyptian equity market was segmented from the rest of the world2. Based on

their results and the fact that the existence of the cointegrating vector between the

US and CSE hinges on the number of lags selected, it is unlikely to conclude that

the Egyptian and US equity markets are integrated. Also, the finding of no

2 Darrat and Hakim (1997) investigated the integration of MENA stock markets including theCSE between Jan 1996 and Mar 1997, the latest available data at the time. More updates areavailable in Darrat and Hakim (2000) and Hakim and Neaime (2000).

19

Tests of Cointegration between CSE and other Equity MarketsMay 95 - May 2000 (weekly) 8 lags

Log Likelihood by Model and RankData Trend: None None Linear Linear Quadratic

No Intercept Intercept Intercept Intercept InterceptNo Trend No Trend No Trend Trend Trend

CSE and LondonRank of Cointeg Vects 0 -1837.445 -1837.45 -1835.44 -1835.44 -1835.19

1 -1834.199 -1833.79 -1832.9 -1829.82 -1829.582 -1833.373 -1832.54 -1832.54 -1827.29 -1827.29

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Paris

0 -1889.617 -1889.62 -1887.41 -1887.41 -1886.451 -1887.051 -1886.88 -1885.38 -1882.91 -1882.652 -1885.976 -1885.27 -1885.27 -1880.89 -1880.89

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Other Emer Mkts

0 -1597.984 -1597.98 -1597.52 -1597.52 -1597.251 -1596.427 -1596.2 -1595.81 -1594.21 -1593.942 -1596.423 -1594.91 -1594.91 -1592.62 -1592.62

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Amman

0 -1186.149 -1186.15 -1184.42 -1184.42 -1184.291 -1183.344 -1183.31 -1182.01 -1177.13 -1177.122 -1183.34 -1180.91 -1180.91 -1175.21 -1175.21

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Casa

0 -1367.823 -1367.82 -1366.91 -1366.91 -1365.441 -1366.68 -1365.78 -1365.56 -1364.15 -1363.072 -1366.218 -1364.66 -1364.66 -1362.95 -1362.95

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Istanbul

0 -1759.838 -1759.84 -1759.4 -1759.4 -1758.171 -1758.421 -1757.28 -1756.85 -1756.4 -1755.742 -1758.42 -1756.05 -1756.05 -1754.03 -1754.03

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and Tel Aviv

0 -1410.715 -1410.72 -1410.29 -1410.29 -1409.851 -1408.752 -1408.73 -1408.31 -1404.23 -1404.062 -1408.546 -1406.86 -1406.86 -1402.26 -1402.26

L.R. Test: Rank = 0 Rank = 0 Rank = 0 Rank = 0 Rank = 0CSE and US

0 -1859.859 -1859.86 -1853.19 -1853.19 -1852.761 -1852.462** -1852.46 -1850.88 -1847.11 -1847.12 -1851.265 -1850.79 -1850.79 -1844.9 -1844.9

L.R. Test: Rank = 1 Rank = 0 Rank = 0 Rank = 0 Rank = 0Significant at 5%Normalized Cointegrating Equation: CSE = .044312 * US

(0.09067)

20

cointegration with other MENA markets is interesting. It indicates that CSE does

not share stochastic links with its regional counterparts and therefore it offers risk

and returns profiles that are unique in the region.

As in the previous section on causality, we also conducted cointegration

analysis between 2 prominent MENA stock markets and the US. The results (also

available from the author on request) confirm the fact that Istanbul and Tel Aviv

share each a unique and stable long-term relation with the US. Consequently, the

weak link, if any, that CSE maintains with the US is evidence of an equity market

that follows a natural growth of establishing itself among more mature stock

markets.

7. SHORT- AND LONG-TERM PRICE DYNAMICS OF CSE:

If accepted, the presence of cointegration between the US and CSE implies,

by virtue of Granger’s (1991) Representation Theorem, that Granger-causality

must exist between the two markets in at least one direction, a result we proved in

a one way causality emanating from the US to the CSE. In this section, we try to

capture long- and short-term dynamics of the CSE by incorporating the

cointegrating equation directly in a Granger causality framework, where each

variable is regressed on its own lags and those lags of the other variable. To

examine the causal linkages between the US and CSE, we specify and estimate a

vector error-correction model (VECM) of the form:

∑ ∑

∑ ∑

−−−

−−−

∆+∆++=∆

∆+∆++=∆

i jjtit

i jjtit

USdCSEcECbaUS

USdCSEcECbaCSE

212112121

111111111

)(

)(

where EC-1 is the (one period lagged) error-correction term distilled from

Johansen’s efficient estimations, e’s are disturbance terms, and ∆ denotes first-

difference required to induce stationarity for the corresponding variables. As

21

Short and Long-Term Dynamicsof the CSE and Links with the US

Mar 95-2000 (weekly)3 lags – D(.) represents first time difference

t-stat in italicsCointegrating Equation

CSE(-1) 1

US(-1) -0.097-1.310

Constant -79.066

Coint Eq. Coefficient* -0.014-1.83

D(CSE(-1))** 0.261-4.260

D(CSE(-2)) 0.043-0.682

D(CSE(-3)) 0.184-2.963

D(US(-1))* 0.029-1.707

D(US(-2)) -0.015-0.917

D(US(-3))** 0.042-2.428

VAR Constant 0.069-0.209

Adj. R-squared 14.2% Log likelihood -778.79 Schwarz SC 6.21* and ** significant at 10% and 5% respectively

Granger (1988) points out, neglect of the error-correction term when modeling

cointegrated variables leads to serious biases due to filtering out low-frequency

(long-run) information. Another advantage of specifying and estimating the above

VECM is that two sources of causality can be identified. First, there is the

22

traditional channel of short-term causality through lagged independent variable

and the additional long-term causality through the error-correction channel (EC).

Table 7 reports the t-statistics we obtain from estimating the above VECM as it

pertains to the CSE only since the VAR equation for the US is not relevant for this

study. It appears that the cointegrating equation is significant in explaining the

movements of the CSE over time. This confirms the earlier results that Egyptian

and US equity markets are integrated. The coefficient of the cointegrating equation

represents the speed of adjustment in stock prices in Egypt to the long-term

relation they share with their counterparts in the US. The US equity prices also

have an impact on the short-term dynamics of stock prices on the CSE (both the 1st

and 3rd lagged US price changes are significant).

Taken together, the VECM results seem to suggest that, despite its relative

infancy, Cairo is integrated with the US equity market suggesting that US prices

can help explain (and therefore forecast) the movements of Egyptian stocks over

time. Obviously, this result has a double-edge to the extent that movements

which originate in the U.S. stock market spillover to Cairo, regardless of their

direction. It is therefore very possible that a bear market in the US causes a

downturn in equity prices on the CSE.

8. CONCLUSION

This study analyzed the properties of the CSE and its links with other

equity markets in the MENA region and elsewhere. Preliminary analysis of its

weekly time series during the past 5 years showed that prices were highly

autocorrelated. These autocorrelations do not die off quickly hinting that

exogenous shocks impacted their prices for a long time. These findings lead us to

base our subsequent analysis on returns as opposed to stock market prices. A plot

of return histograms indicated that their distribution had significant departures

from normality in terms of skeweness and leptokurtosis.

23

Next, we turned our attention to the examination of linkages and spillover

effects. Our results suggest that stock prices on CSE follow a random walk, an

important property of efficient markets. Causality tests also demonstrated the

existence of regional links between CSE and Amman, Istanbul and Tel Aviv. In

order to investigate long-term links, pairwise cointegration analysis between CSE

and 8 other stock markets was performed. The results indicate that CSE does not

have a stable and long-term relation except with the US market. The implication

of this result for international portfolios is that CSE, like other growing emerging

markets, obeys the ‘law of one price’ across its borders and is integrated with the

US equity market. Essentially, for Egypt this means that product and factor prices

are likely to be equalized by the forces of arbitrageurs who exploit any price

disparity between it and the US. Surely, restrictions on capital flows and trade

barriers would metastasize the integration of CSE with other markets. It is

therefore not surprising to find that since 1992, the Egyptian capital market has

experienced major steps towards privatization and trade liberalization.

24

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