Evolution of Inter and Intra-Regional Linkages to MENA Equity

Market

Eric Girard

and

Eurico Ferreira

IntroductionMellon Capital:”Our global tactical and strategic

asset allocation products…invest in developed country markets…and treat other less liquid

markets as a block…”An important question examined in this paper is

whether or not thin emerging capital markets such as MENA capital markets should be treated as a block in a global strategic or tactical portfolio.

The proximity (geographic, culture, religion, etc.) of the countries may lead one to conclude that there is a close connection between their economies hence, susceptibility to be sensitive to shocks from neighboring countries.

MENA Markets: some issues• Wars, political turmoil, economic instability and

institutional underdevelopment have traditionally been powerful obstacles to an increased access to MENA capital markets.

• Small capital markets with recent economic and financial development geared towards an increase in openness to foreign investors.

• During the nineties, Egypt, Israel, Jordan, Lebanon, Morocco, Tunisia and Turkey have been progressively lifting foreign investors’ ownership, and capital and dividends repatriation restrictions. Even the traditionally closed Gulf Country Council markets have become more accessible to foreign investors through international funds and trusts.

MENA Capital Markets overview (2000)Country Market Cap.($ Billion) #Stocks Bahrain 6.6 41 Egypt 28.5 1076 Israel 66.8 665 Jordan 4.95 163 Kuwait 19.8 86

Lebanon 1.58 13 Morocco 10.9 53

Oman 3.46 133 S.Arabia 73 80 Tunisia 2.80 44 Turkey 69.5 315

Asia 2,607 >8,000E EUR 5,879 >8,000E EEU 93 >800E LA 250 >1,300E NA 10,088 >8,000E

Financials: MENA Vs. G7 and other EM countriesCountry Mean Std. Dev Correlation

Bahrain -17.38% 8.63% 0.009

Egypt 3.66% 22.09% 0.003

Israel 5.01% 26.39% 0.387

Jordan -0.80% 12.28% 0.016

Kuwait 6.07% 11.23% 0.002

Lebanon -13.01% 15.90% 0.006

Morocco 6.35% 11.73% 0.002

Oman -26.64% 13.38% -0.009

Saudi Arabia 4.32% 14.45% 0.056

Turkey -1.06% 54.05% 0.132

Tunisia 2.41% 10.88% -0.008

EM -0.55% 16.27% 0.494

World 6.02% 12.29% 1.000

G7 5.89% 12.78% 0.992

Lit. Review stuff• Abraham, Seyyed and Al-Elg (2001) study Bahrain, Kuwait

and Saudi Arabia using monthly index returns from 1993 to 1998, and observe low or negative correlations between markets5 years, 3 markets, 60 data points

• Omran and Gunduz (2001) use a multivariate cointegration methodology and find no long term stochastic trends between Jordan, Turkey, Egypt, Israel and Morocco from January 1996 to June 19993.5 years, 5 markets, 42 data points

• Darrat, Elkhal and Hakim (2000) find long-term bivariate cointegrative relationships for Morocco-Egypt and Morocco-Jordan, but no multivariate cointegrative relationships between the three capital markets from October 1996 to August 1999 2.8 years, 5 markets, 34 data points

Motivation and research questions• Previous studies small samples, few markets

inexistence of intra-regional long-term (stochastic) price linkages.

• Remaining questions to be answered:– Any intra-regional spillovers (short-lived linkages)? – Any inter-regional spillovers between MENA capital

markets and other regional blocks? – Any spillovers from the three major international

financial crises that occurred during the 90s? – Evolution of short-run price linkages that reveal a

globalization trend as observed with most emerging markets during the 90s?

Data• 11 MENA markets (Bahrain, Egypt, Israel, Jordan, Kuwait,

Lebanon, Morocco, Oman, Saudi Arabia, Tunisia, and Turkey) and 5 regional indices (Asia AC, Europe, East Europe, Latin America AC, and North America)

• Daily, weekly and monthly frequency Index series (MSCI, IFC, Local Datastream); Span: 1990 to 2001; also all data are in US Dollarscurrency risk set to zero.

• Spillover study is done using daily data:– Capture potential short-lived interactions—I.e.capital movement

are intrinsically short-term occurrencesFinancial information networks are capable of disseminating news instantaneously around the world, a shock in a national stock market can be transmitted to another market within a very short period of time.

– Many of our series have less than eight years in coverageserious methodological issues with using too few data points.

– Test results could be affected by infrequent trading.

Methodology• 2 Market Linkage issues:

– Global Strategic Asset Allocation (GSAA): Long horizon Cointegration analysis

• Series are I(1)?Tests of stationarity (ADF and KPSS)

• Bilateral cointgration (long term bivariate conintegrative relationship)

• Multilateral cointegrationLong-term common stochastic trends

– Global Tactical Asset Allocation (GTAA): Short Horizon Spillover Issue: Pooled restricted GARCH-VAR methodology on price differences-I(0).

• Generalized Variance decomposition function (%endogenous and %exogenous of total variance forecast)SIZE

• Generalized Impulse Response function: forecast the effect of 1 SD shock in ALL endogenous variable SIGN, TIMING

• Block Exogeneity Granger CausalityPREDICTABILITY

• Geweke CausalityINSTANTANEOUS SPILLOVER

• Dynamic of spillovers: Pooled methodology

Long-term Stochastic Trend (we need to go through this one before we do the fun stuff)

Bilateral Cointegration Results:

•Intra-regional long term linkages (4 out of 55)

–Bahrain-Jordan; Israel-Turkey; Morocco-Saudi Arabia; Morocco-Tunisia

• Inter-regional long term linkages (6 out of 55)

–Israel-North America; Morocco-North America; Saudi-Arabia-North America; Tunisia-North America; Kuwait-East Europe; Tunisia-Europe

•Multivariate cointegration analysis: No common stochastic trends; reverse cointegration tests (Hansen and Johansen, 1999) support findings

•Cointegration tests reveal some pairwise but no common stochastic trends to all MENA markets—i.e., no long-run co-movements

1

10

k

itititt stufftrendotherxyx

GARCH-VAR:

• “Diagonal” VAR-GARCH (see Engle and Sheppard, 2001). By including a GARCH process for each equation of the VAR heteroskedasticity is gone—i.e., the greatest drawback of the VAR methodology.

• Covariances (as in an MGARCH model) are assume to be negligible so that our (Quasi) likelihood estimator will not die on us—i.e., an MGARCH-VAR with 16 variables would require us to estimate, 16 AR equations, 16 variance equations, and 120 covariance equations.

21,

2,

2,

,

1

1,,

1,

tjtjtj

tj

p

iitjji

nj

jtj

e

eSS

This is a system, so variables are vectors

Then, What? And How?

• AmplitudeGVDF

• SignGIRF

• TimingGIRF

• Direction– Granger Causality

(Lead-lag)– Geweke Causality

(contemporaneous)

Dynamic processVARGARCH is pooled forwardmultitude of GARCH-VAR…over time.multitude of GVDF, GIRF, GC and Geweke stuff…over time.

Generalized Variance Decomposition Summary

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Jordan with MENA Turkey with MENA Israel with MENA Egypt with MENA

Kuwait with MENA Morocco with MENA Lebanon with MENA Saudi Arabia with MENA

Tunisia with MENA Bahrain with MENA Oman with MENA

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Jordan with Regional Turkey with Regional Israel with Regional

Egypt with Regional Kuwait with Regional Morocco with Regional

Lebanon with Regional Saudi Arabia with Regional Tunisia with Regional

Bahrain with Regional Oman with Regional

Proportion of exogenous variance coming from MENA

Proportion of exogenous variance coming from Blocks

GIR Intra-regional Exogenous Shocks: Israel

-1

-0.5

0

0.5

1

1.5

2

2.5

1 3 5 7 9 11 13 15 17 19

D(BA) D(EG) D(IS) D(JO) D(KU) D(LE) D(MO) D(OM) D(SA) D(TK) D(TU)

GIR Intra-regional Exogenous Shocks: Morocco

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 3 5 7 9 11 13 15 17 19

D(BA) D(EG) D(IS) D(JO) D(KU) D(LE) D(MO) D(OM) D(SA) D(TK) D(TU)

GIR Intra-regional Exogenous Shocks: Jordan

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 3 5 7 9 11 13 15 17 19

D(BA) D(EG) D(IS) D(JO) D(KU) D(LE) D(MO) D(OM) D(SA) D(TK) D(TU)

GIR Inter-regional Exogenous Shocks: Israel

-0.5

0

0.5

1

1.5

2

2.5

1 3 5 7 9 11 13 15 17 19

D(IS) D(AS) D(EU) D(EAST) D(LA) D(NAM)

GIR Inter-regional Exogenous Shocks: Morocco

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 3 5 7 9 11 13 15 17 19

D(MO) D(AS) D(EU) D(EAST) D(LA) D(NAM)

GIR Inter-regional Exogenous Shocks: Jordan

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 3 5 7 9 11 13 15 17 19

D(JO) D(AS) D(EU) D(EAST) D(LA) D(NAM)

Summary of shocks: GIRF

Intra-Regional (Exogenous) Size Timing

Israel, Turkey Large High persistence

Morocco, Bahrain, Egypt, Kuwait, Lebanon, Oman, Tunisia

Large Rapid decay

Jordan, Saudi Arabia Small Rapid decay

Inter-regional (Exogenous) Size Timing

Israel, Turkey Large Rapid Decay

Morocco, Bahrain, Egypt, Kuwait, Lebanon, Oman, Tunisia

Small Rapid Decay

Jordan, Saudi Arabia Inexistent Rapid Decay

Endogenous shocks Size Timing

Israel, Turkey Large Rapid Decay

Morocco, Bahrain, Egypt, Kuwait, Lebanon, Oman, Tunisia, Jordan, Saudi Arabia

Large High persistence

The more integrated economies of Israel and Turkey seem to process information flows from global markets and act as conduits to other, smaller, MENA markets.

Causality Analysis• Granger causality(lead-lag): Consistent with GVDF, No feed back

relationships• Geweke causalitycontemporaneous relationship

– Most of the residuals correlation coefficients are positive investors view other regional economies as prone to different events.

– Residuals correlation are negative for four GCC market, indicating that capital tend to flow naturally from one market to another. Similar findings by Hassan (2003) who examines linkages among Bahrain, Kuwait and Oman stock markets from October 1994 and August 2001.

– Increase in contemporaneous spillover from other regional blocks– Interesting case of Turkey and Israel increasing amount of

contemporaneous spillovers between Israel and the five regional indices lead-lag spillover analysis fails to capture existing linkages that have become increasingly contemporaneous. The same conclusions can be drawn from Turkey and to a lesser extent for Morocco and Tunisia.

Conclusion

Results from using the IR and VD functions illustrate a striking feature of MENA markets, namely the slow and small transmission of shocks during any period of this study. Results of our four spillover tests (Granger, GIRF, GVDF, residuals correlation, and Geweke) provide evidence that MENA markets are gradually opening to other regional and trans-continental economies, but remaining highly segmented (to the exception of Turkey and Israel) and perhaps predictable. In this case, tactical asset allocation strategies across MENA markets can be beneficial.