The contagious Effect of the US Subprime Crisis on Gulf Countries

Presented by Sana Khelifi

MASTER’S THESIS IN ACTUARIAL & FINANCIAL SCIENCES

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‘When the United States sneezes, the rest of the world may well catch a cold’ – By Rich Miller

Presentation Outline

Motivation

Literature Review

Contagion channels of the Subprime Crisis

Evidence of contagion: Gaussian Copula

Caveats and Conclusion

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Motivation

Since the 1990s, we’ve experienced numerous financial crises:

The Exchange Rate Mechanism attack – 1992 -93 East Asian crises – 1997 Russian Collapse and LTCM – 1998 Brazilian devaluation – 1999 IT bubble - 2000-01 US Sub-prime mortgage crisis – 2007 Aftermath of sub-prime mortgage crises – Early 2008-

09!! Each crisis spreads around like a contagious disease

sometimes without any fundamental explanation4

MotivationContagion? The situation in which a faltering economy in one country

causes otherwise healthy economies in other countries to have financial problems

“..a significant increase in cross-market linkages after a shock to one country (or group of countries)” – Forbes & Rigobon (2001)

Subprime, Contagion…Gulf? The Subprime crisis although originated in a very

specific and relatively small segment of the US mortgage market, it has spread across the borders.

The limited gulf exposure to Subprime instruments (S&P).5

MotivationGulf Stock Market Crash

Gulf as an oil-based state?

Oil prices fell over 75%

6

Gulf Stock market fell over 40 %

KSE

ADIDFM

TASI

MotivationSubprime Crisis – Oil freefall

KSE

ADIDFM

TASI

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Oil prices fell over 75%

Gulf as an oil-based state?

Motivation

Is the US Subprime Crisis contagious to Gulf Market??

What are the potential channels that could move

the US Subprime to Gulf market?

Assuming the definition of Forbes & Rigobon, is

there any significant change in dependence

structure between US and Gulf market after the

Subprime burst?8

Literature Review Fundamental-Based Contagion (non-crisis contingent theories)

It consists of real linkages and interdependencies that already

exist before crisis:

Trade links: country crisis effect on its trading partners’

accounts

Financial links: cross-country investments

Common and random shocks: interest rate surge, oil prices

volatility…

Policy coordination: effect of a member country shock on

other members 9

Literature Review

Pure /Psychological Contagion (crisis

contingent theories)

It consists of channels that differ from those before crisis:

Multiple Equilibrium - Change in investor’s

expectation

Endogenous Liquidity shocks - Portfolio re-allocation

Political contagion 10

Literature ReviewDetection method of contagion?

Fundamental-based contagion measures : Testing the significance of each fundamental transmission channel using binary

probit model - Eichengreen and al. (1996) Pure contagion measures: Testing the structural change in

transmission mechanisms

GARCH & ARCH models – testing the volatility spillover across

market - Edwards (1998)

Dependence measures – testing the change in dependencies after

shock

• Pearson’s linear correlation - King and Wadhwani (1990)

• Conditional correlation - shift contagion - Forbes & Rigobon

(2000)

• Copula approach – Paulo et al. (2009) & Rodriguez (2006)

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Subprime Contagion: Fundamental-based contagion

Financial links – The securitization and its domino effect

SubprimeSubprime BorrowerBorrower

SubprimeSubprime LenderLender

SPVSPV

InvestorsInvestors

Banks

Hedge Funds Insurance Companies

Pension Funds

Housing Prices DeclineARM resets

Mortgage Loans

Sales of loans LoansProceeds

Stop Repayment: Mortgage Delinquencies & Foreclosures

Mortgage Cash Flow declines

-Losses on MBS & CDO-CDS Losses -Asset Prices Collapse-Wave of Corporate defaults-Meltdown in the "Shadow financial

system"-Drying-up of liquidity and capital=> Vicious circle of losses, capital fall,

and credit tightening forced the liquidation and fire sales of assets at below fundamental prices

Securitization

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Fundamental-based contagion - Financial links

GCC credit default swapsGCC real estate price index

Gulf Banks Write-downs

272

740

1200

966

446

0 200 400 600 800 1000 1200 1400

Abu Dhabi Commercial Bank

Gulf Investment Corp.

Gulf International Bank

Arab Banking Corporation

Gulf Bank, Kuwait

Million $

Gulf Sovereign Wealth Funds Losses

Dec 2008 Estimates

-41%

-40%

-36%

-30%

-12%

-50% -40% -30% -20% -10% 0%

ADIA

KIA

Norwegian Oil Fund

QIA

SAMA

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GRC

IMF

IMF

GRC

IMF

IMF

Fundamental Based-contagion Trade Links

-2000

-1500

-1000

-500

0

500

1000

1500

NorthAmerica

Europe FormersSoviet Union

Middle East Asia LatinAmerica

Africa

2007 2008 2009

Source: IEA

Oil demand down,…

Fundamental-based contagion Common Aggregate shock

The Fed Interest rate hike

rising of spreads and finance costs, Loans Defaults –

Credit default swaps hike

Weak US dollar - GCC currencies peg to US dollar

Oil prices fall - Gulf as oil-based states

Growing Inflation

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Pure / Psychological contagion

Gulf investors sensitivity to signs of economic weakness

Change In Stock Market Indices

-73%

-57%

-50%

-49%

-47%

-46%

-44%

-42%

-80% -70% -60% -50% -40% -30% -20% -10% 0%

Dubai

Saudi Arabia

Qatar

Oman

Kuwait

S&P500

Abu Dhabi

Bahrain

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IMF

Evidence of contagion - Gaussian Copula

Data: daily return indices issued from the US stock

market and three other GCC markets: S&P500, DFM, KSE

and TASI index

Period: 1st of January 2005 to the 05th of February 2009

Numbers of Observations:

Programming tool: Matlab (v 7.0)

S&P500 DFM KSE TASI

Total Nos. of Obs.

1031 1097 1055 1089

Pre-crisis. Nos. 649 729 663 715

Crisis Nos. 382 368 392 374

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Data analysis

Daily return indices

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Data analysis

Descriptive Statistics

Histograms goodness of fit

S&P500 DFM KSE TASI

Mean. -0.0003 -0.00029 -0.00017 -0.00012

Std. 0.0146 0.0179 0.0079 0.0186

KurtosisSkewness

16.1492-0.345

10.9134-0.0132

9.4178-0.7957

9.4983-0.7822

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-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.150

20

40

60

80

100histogramme DMF

-0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05 0.060

20

40

60

80

100histogramme KSE

-0.15 -0.1 -0.05 0 0.05 0.10

20

40

60

80

100

120histogramle TASI

-0.1 -0.05 0 0.05 0.1 0.150

50

100

150

200histogramme SP500

Methodology

Select the Univariate Distribution Functions

appropriate for each index: We test the Gaussian & t-

student functions

Select the appropriate copula to Join the marginal

distributions taken in step1

Divide the series into two sub-periods: “pre-crisis

period” and “crisis period”

Estimate the parameters of the selected copula taken

in step 2

and compare between the pre-crisis and crisis period.20

Results

T-student function has been selected as the adequate univariate distributions for all of the indices (as shown the qqplot below and as per the Maximum likelihood

estimations)

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-0.1 -0.05 0 0.05 0.1

0.00010.00050.001 0.005 0.01 0.05 0.1 0.25 0.5 0.75 0.9 0.95 0.99 0.995 0.999 0.99950.9999

Data

Pro

bability

DMF data

Normalestudent

-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08

0.00010.00050.001 0.005 0.01

0.05 0.1

0.25

0.5

0.75 0.9 0.95

0.99 0.995 0.999 0.99950.9999

DataP

robability

TASI data

Normal TASIStudent TASI

-0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05

0.00010.00050.001 0.005 0.01

0.05 0.1 0.25

0.5

0.75 0.9 0.95

0.99 0.995 0.999 0.99950.9999

Data

Pro

bability

KSE data

StudentNormal

-0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1

0.00010.00050.001 0.005 0.01 0.05 0.1 0.25 0.5 0.75 0.9 0.95 0.99 0.995 0.999 0.99950.9999

Data

Pro

bability

SP data

Normal SPstudent SP

Results

Gaussian Copula has been selected as per the scatter plot of indices.

• The set of points is highly

concentrated and centered

•The scatter of the points seems to

be relatively alike in the left and

upper tail 22

SP500 vs DMF

-15.00%

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

-15.00% -10.00% -5.00% 0.00% 5.00% 10.00% 15.00%

SP500

DM

F

SP500 vs TASI

-15.00%

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

-15.00% -10.00% -5.00% 0.00% 5.00% 10.00% 15.00%

SP500

TA

SI

SP500 vs KSE

-5.00%

0.00%

5.00%

10.00%

-15.00% -10.00% -5.00% 0.00% 5.00% 10.00% 15.00%

SP500

KS

E

Results

Based on the fundamental event (burst of the subprime bubble) and the empirical perception shown below, the 1st of August 2007 has been chosen as the structural break date separating between the pre-crisis period and the crisis period.

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Results

Copula parameters have increased significantly from the pre-crisis to crisis period for all the indices under investigation.

Saudi Market displays stronger signs of contagion

There is an evidence for the presence of contagion between the American Market and the Gulf markets under investigation.

Estimated copula parameters

Whole period Pre-crisis

periodCrisis period

DFM 0.0257 -0.037 0.0772

KSE 0.0379 0.0044 0.0772

TASI 0.0505 -0.0119 0.1285

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Caveats and Conclusion

This study tests for financial contagion impact of the US Subprime

crisis on Gulf economies both theoretically and empirically.

Theoretically, it investigates the possible connections that could

move the Subprime crisis to the Gulf market, by identifying the

bridge of channels between the US and GCC countries.

Fundamental channels: the securitization, oil channel and some

other commons shocks like the Fed interest rate and the US dollar.

Psychological channels: the herding behavior due to the shift in

investor sentiment which is manifested by the massive liquidation

and capital outflows.

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Caveats and Conclusion

Empirically, Gaussian Copula has been used to analyze the

change in dependence structure from the pre-crisis to the crisis

period. Results show significant level of contagion in Kuwait,

Dubai stock markets and Saudi market which displays the

strongest level.

Contagion signs should be taken into consideration by the

portfolio managers (ineffectiveness of the diversification

strategies)

Our results can be handy for Gulf central banks who decide for the

bailout.

Some limits:

Theoretically: Lack of transparency and sophistication in gulf

markets

Empirically: one Gaussian copula out of many was adopted basing

on graphical insight.

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