The Anatomy of Financial Crisis

7/28/2019 The Anatomy of Financial Crisis

1/16

THE ANATOMY OF FINANCIAL CRISIS: EVIDENCE FROM THE

EMERGING MARKETS

*Anindita Chakraborty**Alok Shrivastava***Ravindra Pathak

Abstract

We study the anatomy of recent financial crises in India, Indonesia, Malaysia, Spain, Brazil,

Chile, Italy, Switzerland and Argentina by investigating the return and volatility before the

financial crisis and during recession. We use the date of Lehman Bankruptcy case as a proxy of

financial crisis (15th

September, 2008). Parametric technique was used to test the significantdifference before the financial crisis and during the crisis. Our analysis produced mixed results

indicating that there is a significant impact of financial crisis on countries like Indonesia, Italy,

Brazil, Argentina and Spain.

Keywords: Financial Crisis, volatility, return


2/16

IntroductionThe 20th century faced with the worlds two major financial crises. The first global financial

crisis was seeing during 1929-30, which affected the developed nations, Europe and Americaand the second during 2007-till continued had affected the whole international community. More

and more people will be affected by it both directly and indirectly and the full scale of the crisis

either economically or socially has not been measured till now. The emerging financial marketsor the developing countries has not been left beset by current episode of turmoil of LehmanBrother Bankruptcy most notably originating in U.S at the end of the year 2008. The term

emerging markets is used to describe a nation's social or business activity in the process of rapid

growth and industrialization. The impact of the current financial crisis poses several interestingquestions for the international community and for those involved in policy making in the

development community. In immediacy of the occurrence of the financial crisis one of the most

severe crisis after Great Depression, most emerging and some of the developed markets

experienced sudden and severe downward movements in stocks. These markets are also felt theliquidity crunch, rapid reversals of capital flows, significant output losses, bank runs, or spillover

effects. The deliberation of these episodes of instability usually referred to as financial crises.

This situation of shrinking global economy is indeed a wakeup call for the internationalcommunity in general and developing countries in particular.

This impact of the global financial crisis has been more severe for emerging markets than for

lowincome countries, which are less integrated into international private capital markets. As in

2003-2007, the emerging markets experienced an impressive economic boom with a growth rate

of 7% per year. The boom was due to the mix results of the following ingredients prevailing in

global markets and that were exceptional financing, high commodity prices, foreign directinvestment and, large flows of remittances. These conditions have been replaced since mid-2008,

particularly since September 2008, by the effects of financial turmoil that erupted in mid-2007 in

the U.S. and resulted in the worst global financial crisis and the worst recession since the Great

Depression. The current international financial crisis has its roots in the subprime crisis in theUnited States. The excessive growth of subprime lending occurred because financial institutions

offered non-standard mortgages to individuals with dubious credit profiles and due to this,

countries like India and Taiwan saw negative portfolio investment flows. In Latin America,

Brazil and Mexico were also hit by losses in derivative markets and, in the first case, by theunwinding of the carry trade. South Africa was also severely hit. It severely affected the bond

markets and due to this it came to a halt, bank lending was also get affected, and there was a

sharp reversal of flows from mutual funds and an unwinding of the carry trade. This behavior ofthe quantity and price of financial flows has been a major mechanism transmitting movements in

stock markets from industrial to developing countries. On an average, when measured in dollar

terms, stock markets have experienced a stronger contraction in emerging markets since their

peak in late October

early November 2007 than stock markets in industrial countries.

In this paper we tried to find out the impact of the financial crisis on the emerging markets stock

exchanges like India, Indonesia, Malaysia, Spain, Italy, Switzerland, Brazil, Argentina, and

Chile, which were further grouped into continents like Asia, South America, and Europe.


3/16

Review of LiteratureThe various theoretical and empirical literature suggested that financial crises have alternatively

been attributed to local macroeconomic and microeconomic weaknesses (Krugman, 1979;Agenor et al., 1992; Kaminsky et al., 1998), coordination problems among investors (Chang and

Velasco, 1999), the activity of large traders and speculators (e.g., Brown et al., 2000; Kyle and

Xiong, 2001), the interaction of stock and foreign exchange markets (Corsetti et al., 1999; Parkand Lee, 2003), or crisis is spread from one country to the other generating the contagionphenomenon (Boyer et al., 2006; Pasquariello, 2007) as reviewed by Pasquariello (2008).

Demyanyk and Hemart (2008) found that the quality of bank loans deteriorated for sixconsecutive years before the crisis and that securitizers were, to some extent, aware of it. They

further provided evidence that the rise and fall of the subprime mortgage market follows a classic

lending boom-bust scenario, in which unsustainable growth leads to the collapse of the market.

Hoontrakul (2008) said that the global financial crisis was caused by extra risk taken by bankingsystem and credit markets of US. Past boom and bust cycle caused by excessive speculation was

localized and caused by exogenous risk, financial institution reacted to the high uncertainty,

banks stop lending to each other. Credit freeze and liquidity crunch, quantitative monetaryeasing, coordinated rate cut around the world and liquidity injection from the government may

stem the panic and only stabilized the financial market, not found quick end to the worldwide

recession.

Similarly Kenourgios et al. (2008) showed that a crisis episode spreads with a large magnitude

even though some countries belong in different regional blocks. The finding had important

implications for international investors, returns and volatilities shows higher correlations amongstock markets, leaving international investors exposed to unhedged risks. However Mohan

(2008) said India had by-and-large been spared of global financial contagion due to the subprime

turmoil for a variety of reasons and that were Indias growth process depends on largely

domestic demand driven and its dependence on foreign deposits had remained around 1.5% inrecent period. The credit derivatives market was in an embryonic stage; the originate-to-

distribute model in India was not comparable to the ones prevailing in advanced markets; there

are restrictions on investments by residents in such products issued abroad; and regulatoryguidelines on securitization did not permit immediate profit recognition. Financial stability in

India had been achieved through perseverance of policies which prevented institutions from high

risk taking, and financial markets from becoming extremely volatile and turbulent.

In the studies related to financial crisis and its impact on share it was reported by Bertero and

Mayer (1989) and King and Wadhwani (1990) that increase in stock returns correlation in 1987

crash. Calvo and Reinhart (1996) reported that correlation shifted during the Mexican crisis.Baig and Goldfajn (1999) in their study found significant increases in correlation for several East

Asian markets and currencies during the East Asian crisis, supporting the contagion

phenomenon.


4/16

OBJECTIVES OF THE STUDY1. To evaluate and compare the returns of emerging stock exchanges before financial crisis and

during recession.2. To evaluate and compare the volatility of emerging stock exchanges before financial crisis

and during recession.

3.

To compare the volatility of emerging stock exchanges of different continents.4. To compare the returns of emerging stock exchanges of different continents.5. To open new vistas for further research.DATA AND RESEARCH METHODOLOGY

The main purpose of the study is to examine the impact of the financial crisis on the emergingmarket stock exchanges. The study was empirical in the nature and the total population includes

all the stock exchanges of emerging markets. Hence the stock exchanges index prices were the

sampling elements and the sampling frame of the study was from 2008-2009. The random

sampling technique was used to select the data. The sample size includes nine emerging marketstock exchanges. The event-study methodology was used for analyzing the impact of financial

crisis on the returns and volatility of the sample stock exchange indices. The stock exchangeindex returns and volatilities during recession were compared with their returns and volatilitiesprior to the financial crisis. To analyze the data the study period is divided into the following

event window.

-100 days 0(Event day) +100 days

Daily prices of individual index for an event window of 100 days before and after financial crisis

were taken from the official website of Yahoo finance. The pre-crisis period starts 100 days

before the crisis day to 1 day before the crisis and the post-listing period is from 1 day after the

crisis to 100 days after the financial crisis.

TABLE 1: List of Emerging Market Stock ExchangesAsia Europe South America

India(BSE-Sensex) Spain (Madrid) Brazil (Bovespa)

Indonesia(CompositeIndex JKSE)

Italy (MIBTEL) Argentina (Marvel)

Malaysia (KLSEComposite)

Switzerland(SwissMarket)

Chile (IPSA)

Following tools were applied for data analysis:

The daily returns of the indices were computed by logarithmic returns using MS Excel.Inferential statistics was computed with the help of SPSS 16.

Rt = 100 *ln (Indext / Indext-1)

Where, Rt is the daily mean return percent from the index, P is the price index, t and t 1represent the current and immediate preceding day.

Mean return for each month was computed by applying simple arithmetic mean. Paired sample t-test was applied to find out the significant difference in the index returns.


5/16

Volatility of the index was calculated through standard deviation and F-test was applied tofind out the significant difference between the pre and post volatility.

To test the difference between the returns and volatility of the different countries SPANOVAwas applied.

RESULTS AND DISCUSSIONS

1. Comparison of the returns before and during 100 days of financial crisisH01= There is no significant difference in the returns before and during 100 days of recession.

IndonesiaPaired Samples Statistics

Mean N Std. Deviation Std. Error Mean

Pair 1 PREINDONESIA -.2542 100 1.41510 .14151

POST -.1202 100 1.38116 .13812

Paired Samples Test

Paired Differences

t df

Sig. (2-

tailed)Mean

Std.

Deviation

Std. Error

Mean

95% Confidence Interval ofthe Difference

Lower Upper

Pair 1 PREINDONESIA -POST

-.13398 1.99885 .19988 -.53060 .26263 -.670 99 .504

A paired sample t-test was conducted to evaluate the index returns earn before and after 100 daysof financial crisis in Indonesia. There was a statistically significant increase in the returns of the

index from pre 100 days (M= -0.2542, S.D=1.41510) to post 100 days (M= -0.1202,

S.D=1.38116), t(99)= -0.670, p= 0.504 i.e. more than the 5% level of the significance. So wecan conclude that there was no significant difference in the index returns before and after 100

days of financial crisis and thus the null hypothesis was rejected. Given our eta square statistics

of 0.0025 we can conclude that there was a small effect with substantial difference in the return

statistics scores obtained before and after the financial crisis.

IndiaPaired Samples Statistics


Pair 1 PREINDIA -.2065 100 2.22598 .22260

POST -.4030 100 3.51232 .35123


6/16

Paired Samples Test

Paired Differences

t dfSig. (2-tailed)Mean

Std.Deviation

Std. ErrorMean

95% Confidence Interval of

the Difference

Lower Upper

Pair 1 PREINDIA

POST.19650 4.30871 .43087 -.65844 1.05144 .456 99 .649

A paired sample t-test was conducted to evaluate the index returns earn before and after 100 days

of financial crisis in India. There was a statistically significant increase in the returns of the index

from pre 100 days (M= -0.2065, S.D=2.22598) to post 100 days (M= -0.4030, S.D=3.51232),t(99)= 0.456, p= 0.649 i.e. more than the 5% level of the significance. So we can conclude that

there was no significant difference in the index returns before and after 100 days of financialcrisis and thus the null hypothesis was rejected. Given our eta square statistics of 0.0021 we canconclude that there was a small effect size with substantial difference in the return statistics

scores obtained before and after the financial crisis.

MalaysiaPaired Samples Statistics


Pair 1 PREMALAYSIA -.2447 100 .93185 .09318

POSTMALAYSIA -.1381 100 1.39238 .13924

Paired Samples Test

Paired Differences


Std.Deviation

Std. ErrorMean

95% Confidence Interval of

the Difference

Lower Upper

Pair 1 PREMALAYSIA -POSTMALAYSIA

-.10660 1.66284 .16628 -.43654 .22335 -.641 99 .523

A paired sample t-test was conducted to evaluate the index returns earn before and after 100 daysof financial crisis in India. There was a statistically significant increase in the returns of the indexfrom pre 100 days (M= -0.2447, S.D=.93185) to post 100 days (M= -0.1381, S.D=1.39238),

t(99)= -0.641, p= 0.523 i.e. more than the 5% level of the significance. So we can conclude that

there was no significant difference in the index returns before and after 100 days of financialcrisis and thus the null hypothesis was rejected. Given our eta square statistics of 0.0041 we can

conclude that there was a small effect size with substantial difference in the return statistics

scores obtained before and after the financial crisis.


7/16

SpainPaired Samples Statistics


Pair 1 PRESPAIN -.0551 100 1.07118 .10712

POSTSPAIN -.0926 100 1.58865 .15887


of financial crisis in Spain. There was a statistically significant increase in the returns of the

index from pre 100 days (M= -0.0551, S.D=1.07118) to post 100 days (M= -0.0926,S.D=1.58865), t(99)= 0.194, p= 0.846 i.e. more than the 5% level of the significance. So we can

conclude that there was no significant difference in the index returns before and after 100 days of

financial crisis and thus the null hypothesis was rejected. Given our eta square statistics of

0.0003 we can conclude that there was a small effect size with substantial difference in the returnstatistics scores obtained before and after the financial crisis.

SwitzerlandPaired Samples Statistics


Pair 1 PRESWITZERLAND -.0156 100 1.15532 .11553

POST -.3066 100 2.98116 .29812

Paired Samples Test

Paired Differences

t df

Sig. (2-

tailed)Mean

Std.

Deviation

Std. Error

Mean


Lower Upper

Pair 1 PRESWITZ

ERLANDPOST

.29099 3.13325 .31333 -.33072 .91269 .929 99 .355

Paired Samples Test

Paired Differences

T dfSig. (2-tailed)Mean

Std.Deviation

Std. ErrorMean


Lower Upper

Pair 1 PRESPAIN

POSTSPAIN

.03747 1.92755 .19276 -.34500 .41994 .194 99 .846


8/16


of financial crisis in Switzerland. There was a statistically significant increase in the returns of

the index from pre 100 days (M= -0.156, S.D=1.15532) to post 100 days (M= -0.3066,S.D=2.98116), t(99)= 0.929, p= 0.355 i.e. more than the 5% level of the significance. So we can

conclude that there was no significant difference in the index returns before and after 100 days of

financial crisis and thus the null hypothesis was rejected. Given our eta square statistics of0.0086 we can conclude that there was a small effect size with substantial difference in the returnstatistics scores obtained before and during recession.

ItalyPaired Samples Statistics


Pair 1 PREITALY -.1925 100 1.22256 .12226

POST -.3471 100 3.09372 .30937

Paired Samples Test

Paired Differences


Std.Deviation

Std. ErrorMean

95% Confidence Interval

of the Difference

Lower Upper

Pair 1 PREITALY

POST.15456 3.28830 .32883 -.49791 .80703 .470 99 .639


of financial crisis in Italy. There was a statistically significant increase in the returns of the indexfrom pre 100 days (M= -0.1925, S.D=1.22256) to post 100 days (M= -0.33471, S.D=3.09372),

t(99)= 0.470, p= 0.639 i.e. more than the 5% level of the significance. So we can conclude that

there was no significant difference in the index returns before and after 100 days of financialcrisis and thus the null hypothesis was rejected. Given our eta square statistics of 0.0022 we can

conclude that there was a small effect size with substantial difference in the return statistics

scores obtained before and during recession.

ChileA paired sample t-test was conducted to evaluate the index returns earn before and after 100 days

of financial crisis in Chile. There was a statistically significant increase in the returns of the

index from pre 100 days (M= -0.2185, S.D=2.12320) to during 100 days (M= -0.0014,S.D=1.55391), t(99)= -0.874, p= 0.384 i.e. more than the 5% level of the significance. So we

can conclude that there was no significant difference in the index returns before and after 100


of 0.0076 we can conclude that there was a small effect size with substantial difference in thereturn statistics scores obtained before and during recession.


9/16

Paired Samples Statistics


Pair 1 PRECHILE -.2185 100 2.12320 .21232

POST -.0014 100 1.55391 .15539

Paired Samples Test

Paired Differences


Std.Deviation

Std. ErrorMean

95% Confidence Intervalof the Difference

Lower Upper

Pair 1 PRECHILEPOST

-.21709 2.48350 .24835 -.70987 .27569 -.874 99 .384

ArgentinaPaired Samples Statistics


Pair 1 PREARGENTINA -.3180 100 1.57433 .15743

POST -.3186 100 4.21344 .42134

Paired Samples Test

Paired Differences


Std.Deviation

Std. ErrorMean

95% ConfidenceInterval of the

Difference

Lower Upper

Pair 1 PREARGENTINA- POST

.00056 4.79327 .47933 -.95052 .95165 .001 99 .999


of financial crisis in Chile. There was a statistically significant increase in the returns of the

index from pre 100 days (M= -0.3180, S.D=1.57433) to during 100 days (M= -0.3186,

S.D=4.21344), t(99)= 0.001, p= 0.999 i.e. more than the 5% level of the significance. So we canconclude that there was no significant difference in the index returns before and after 100 days of

financial crisis and thus the null hypothesis was rejected. Given our eta square statistics of

0.0000 we can conclude that there was a small effect size with substantial difference in the returnstatistics scores obtained before and during recession.


10/16

BrazilPaired Samples Statistics


Pair 1 PREBRAZIL -.2938 100 2.09788 .20979

POST -.1398 100 4.63580 .46358

Paired Samples Test

Paired Differences

T df

Sig. (2-

tailed)Mean

Std.

Deviation

Std. Error

Mean

95% Confidence Intervalof the Difference

Lower Upper

Pair 1 PREBRAZILPOST

-.15397 5.19707 .51971 -1.18518 .87724 -.296 99 .768

A paired sample t-test was conducted to evaluate the index returns earn before and after 100 daysof financial crisis in Chile. There was a statistically significant increase in the returns of the

index from pre 100 days (M= -0.2938, S.D=2.09788) to during 100 days (M= -0.1398,

S.D=4.63580), t(99)= -0.296, p= 0.768 i.e. more than the 5% level of the significance. So wecan conclude that there was no significant difference in the index returns before and after 100


of 0.0008 we can conclude that there was a small effect size with substantial difference in the

return statistics scores obtained before and during recession.

2. Comparison of the volatility before and during 100 days of financial crisisThe volatility of the indices which means the relative rate at which the price of an index moves

up and down is shown in table 2. The table reports about the standard deviation before and after

financial crisis of the individual indices. While the F-test was applied to determine whether thereis a significant difference between the pre-financial crisis and post-financial crisis volatility of

the individual indices.

H02= There was no significant difference in the before and during recession volatility.

Table 2: Comparison of Volatility before and during100 days of financial crisis

Indices

Standard Deviation F-test

(5%significance)

(1.683)

Hypothesis Not

Rejected/RejectedPre-

Financial

Crisis

Post-

Financial

Crisis

India(BSE-Sensex) 2.22539 3.50300 1.5741 Not Rejected

Indonesia(CompositeIndex JKSE)

1.486633.07574 2.0689344 Rejected
http://www.investorwords.com/3807/price.htmlhttp://www.investorwords.com/4446/security.htmlhttp://www.investorwords.com/4446/security.htmlhttp://www.investorwords.com/3807/price.html


11/16

Malaysia (KLSE

Composite).91903

1.39238 1.515039 Not Rejected

Spain (Madrid) 1.07849 1.61389 1.49643 Not Rejected

Italy (MIBTEL) 1.22256 3.09372 2.53026 Rejected

Switzerland(SwissMarket)

1.21906 2.98116 2.44545 Rejected

Brazil (Bovespa) 2.09788 5.88428 2.804869 Rejected

Argentina (Marvel) 1.57433 4.21344 2.676338 Rejected

Chile (IPSA) 2.12320 1.55391 1.3669 Not Rejected

The result on the basis of standard deviation before and after 100days of financial crisis showed

increase in volatility after the crisis in all the countries except Chile. For the given values of F,

the values of Indonesia (2.0689344), Italy (2.53026) and Switzerland (2.44545) are more thanthe Standard value, 1.683, at 5% level of significance, so the null hypothesis in that case is

rejected. This shows that there is significant difference in the post and pre listing volatility on

these stocks exchanges. The results also indicated that the volatility of the stock exchanges alsoincreased due to financial crisis.

3. Comparison of the pre and during recession volatility of different continentsTo test the significant difference between the pre and during recession volatility due to financial

crisis we had applied SPANOVA with a factorial design

Box's Test of Equality of Covariance Matricesa

Box's M 2.573

F .346

df1 6

df2 5.608E3

Sig. .913

Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal acrossgroups.

a. Design: Intercept + CONTINENTSWithin Subjects Design: TIME

An insignificant value of Boxs M test showed above that the groups do not differ from each

other we can apply the SPANOVA. A mixed between-within group anova or SPANOVA wasconducted to explain the impact of financial crisis on the indices volatility of the different

continents before and during 100 days of financial crisis. The time period was divided into two

categories pre and during recession and the results of multivariate test which was tested through

Wilks Lambda showed the value 0.539, with a probability value 0.003. Because our p value isless than .05, we can conclude that there was a statistically significant effect for time i.e. pre and

during 100 days of recession. This suggests that there was a change in the volatility due to

financial crisis. Thus the main effect for the time was significant. Although we have foundstatistically significant difference among the time periods, we also need to assess the effect size

of this result which was evaluated through partial eta square. The value obtained for the time in

this study was 0.461. Using the commonly used guidelines proposed by Cohen (1988) (.01=

small effect, .06=moderate effect, .14=large effect), this result suggests a very large effect size.


12/16

In addition to the main effect, we are also required to find out that there was a significant

interaction effect was presented or not. In this the interaction effect was not statistically

significant as the significance level for Wilks Lambda was 0.822 and p= 0.230.

Multivariate Testsc

Effect Value FHypothesis

df Error df Sig.Partial EtaSquared

Noncent.Parameter

ObservedPowerb

TIME Pillai's Trace .461 12.815a 1.000 15.000 .003 .461 12.815 .917

Wilks' Lambda .539 12.815a 1.000 15.000 .003 .461 12.815 .917

Hotelling's Trace .854 12.815a 1.000 15.000 .003 .461 12.815 .917

Roy's LargestRoot

.854 12.815a 1.000 15.000 .003 .461 12.815 .917

TIME *CONTINENTS

Pillai's Trace .178 1.621a 2.000 15.000 .230 .178 3.242 .289

Wilks' Lambda .822 1.621a 2.000 15.000 .230 .178 3.242 .289

Hotelling's Trace .216 1.621a 2.000 15.000 .230 .178 3.242 .289

Roy's Largest

Root.216 1.621a 2.000 15.000 .230 .178 3.242 .289

a. Exact statistic

b. Computed using alpha = .05

c. Design: Intercept + ONTINENTS

Within Subjects Design: TIME

Tests of Between-Subjects Effects

Measure:MEASURE_1

Transformed ariable:Average

SourceType III Sum

of Squares Df Mean Square F Sig.Partial EtaSquared

Noncent.Parameter

ObservedPowera

Intercept 124.992 1 124.992 106.704 .000 .877 106.704 1.000

CONTINENTS 1.202 2 .601 .513 .609 .064 1.026 .119

Error 17.571 15 1.171

a. Computed using alpha = .05

Further the groups (continents) analysis showed that the main effect for the continents was notsignificant as the F (2, 0.513), p= 0.609 which was higher than p=0.05. However the post hoc

comparisons using Turkey HSD test showed below indicated that the mean score for different

countries differ either of the other groups but did not reach the statistically significant level. Thus

we can conclude that there was no significant difference in the pre and during recession volatilityof the three continents and the effect size was also low as showed by partial eta square= 0.064.


13/16

Multiple Comparisons

MEASURE_1Tukey HSD

(I)CONTI

NENTS

(J)CONTI

NENTS

Mean Difference

(I-J) Std. Error Sig.


Lower Bound Upper Bound

1 2 -.3119 .44185 .764 -1.4596 .8358

3 .1222 .44185 .959 -1.0255 1.2698

2 1 .3119 .44185 .764 -.8358 1.4596

3 .4340 .44185 .599 -.7137 1.5817

3 1 -.1222 .44185 .959 -1.2698 1.0255

2 -.4340 .44185 .599 -1.5817 .7137

4. Comparison of the pre and during recession returns of different continents.Box's Test of Equality of Covariance Matricesa

Box's M 4.858

F .653

df1 6

df2 5607.692

Sig. .688

Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across

groups.

a. Design: Intercept + CONTINENTSWithin Subjects Design: PREPOST

An insignificant value of Boxs M test showed that the groups do not differ from each other wecan apply the SPANOVA. A mixed between-within group anova or SPANOVA was conducted

to explain the impact of financial crisis on the indices returns of the different continents beforeand during 100 days of financial crisis. The time period was divided into two categories pre and

during recession and the results of multivariate test which was tested through Wilks Lambda

showed the value 0.084, with a probability value 0.000. Because our p value is less than .05, wecan conclude that there was a statistically significant effect for time i.e. pre and during 100 days

of recession and that means there was a significant difference in the returns of pre and during

crisis period. Thus the main effect for the time was significant. Although we have found

statistically significant difference among the time periods, we also need to assess the effect sizeof this result which was evaluated through partial eta square. The value obtained for the time in

this study was 0.916. Using the commonly used guidelines proposed by Cohen (1988) (.01=small effect, .06=moderate effect, .14=large effect), this result suggests a very large effect size.

In addition to the main effect, we are also required to find out that there was a significantinteraction effect was presented or not. In this the interaction effect was not statistically

significant as the significance level for Wilks Lambda was 0.998 and p= 0.982 as shown in the

below table of multivariate test.


14/16

Multivariate Testsc

Effect Value FHypothesis

dfError

df Sig.

Partial

EtaSquared

Noncent.Parameter

ObservedPowerb

PREPOST Pillai's Trace .916 163.510a 1.000 15.000 .000 .916 163.510 1.000

Wilks' Lambda .084 163.510a 1.000 15.000 .000 .916 163.510 1.000

Hotelling'sTrace

10.901 163.510a 1.000 15.000 .000 .916 163.510 1.000

Roy's LargestRoot

10.901 163.510a 1.000 15.000 .000 .916 163.510 1.000

PREPOST *CONTINENTS

Pillai's Trace .002 .018a 2.000 15.000 .982 .002 .037 .052

Wilks' Lambda .998 .018a 2.000 15.000 .982 .002 .037 .052

Hotelling'sTrace

.002 .018a 2.000 15.000 .982 .002 .037 .052

Roy's LargestRoot

.002 .018a 2.000 15.000 .982 .002 .037 .052

a. Exact statisticb. Computed using alpha = .05

c. Design: Intercept + CONTINENTS

Within Subjects Design: PREPOST

Further the groups (continents) analysis showed that the main effect for the continents was not

significant as the F (2, 0.019), p= 0.981 which was higher than p=0.05. However the post hoccomparisons using Turkey HSD test showed below indicated that the mean score for different

countries differ either of the other groups but did not reach the statistically significant level. Thus

we can conclude that there was no significant difference in the pre and during recession indexreturns of the three continents and the effect size was also low as showed by partial eta square=

0.003.

Tests of Between-Subjects Effects

Measure:MEASURE_1Transformed Variable:Average

Source

Type IIISum ofSquares df Mean Square F Sig.

Partial EtaSquared

Noncent.Parameter

ObservedPowera

Intercept 15.124 1 15.124 97.462 .000 .867 97.462 1.000

CONTINENTS .006 2 .003 .019 .981 .003 .038 .052

Error 2.328 15 .155

a. Computed using alpha = .05


15/16

Multiple Comparisons

MEASURE_1Tukey HSD

(I)CONTIN

ENTS

(J)CONTIN

ENTS

Mean Difference

(I-J) Std. Error Sig.


Lower Bound Upper Bound

1.00 2.00 -.0064 .16082 .999 -.4241 .4114

3.00 -.0297 .16082 .981 -.4475 .3880

2.00 1.00 .0064 .16082 .999 -.4114 .4241

3.00 -.0234 .16082 .988 -.4411 .3943

3.00 1.00 .0297 .16082 .981 -.3880 .4475

2.00 .0234 .16082 .988 -.3943 .4411

Based on observed means.The error term is Mean Square(Error) = .078.

ConclusionThe past financial crises have received increasing attention from the economic and financial

literature, not due to their tremendous social and allocation costs but also due to their impact on

the society in whole. Determining the nature of financial crises is crucial to explaining their

occurrence and formulating policy recommendations so that it can be controlled in the future.But the recent financial crisis which has an immense effect on the whole world failed all the

policy recommendations. The paper tried to find out the impact of the Lehman Brothers

bankruptcy on the stock exchanges of the three continents that were Asia, South America andEurope.

Finally, using several parametric techniques we offered support for some of the available

explanations of financial crises in emerging economies by showing that there was a increase involatility and change in returns before and during financial crisis. T-test results showed that there

was no change in returns before and during recession but the Wilks Lambda showed that there

was a significant difference in the before and during returns of the continents. Similar, resultswere depicted in case of volatility. Thus the study concluded that there was a significant

difference in the volatility of Indonesia, Brazil, Argentina, Switzerland and Italy.

References

Agenor, P., Bhandari, B., amd Flood, R. (1992). Speculative Attacks and Models ofBalance of Payments Crises. IMF Staff Papers, 39, 357394.

Baig, T. and Goldfajn, I. (1999). Financial Market Contagion in the Asian crisis. IMFStaff Papers, 46.

Bertero, E. and Mayer, C. (1989). Structure and Performance: Global Interdependence ofStock Markets around the Crash of October 1987. C.E.P.R. Discussion Papers, No. 307. Boyer, B. H., Kumagai, T. and Yuan K., (2006). How do Crises Spread? Evidence from

Accessible and Inaccessible Stock Indices. Journal of Finance, 66, 957-1003.

Brown, S., Goetzmann, W., and Park, J. (2000). Hedge funds and the Asian currencycrisis of 1997. Journal of Portfolio Management, 26, 95-10.

Chang, R., and Velasco, A. (1999). Liquidity Crises in Emerging Markets: Theory andPolicy. NBER Macroeconomic Annual, 1158.


16/16

Corsetti, G., Pesenti, P., and Roubini, N., (1999).What caused the Asian currency andFinancial Crisis?. Japan and the World Economy, 11, 305373.

Demyanyk, Yuliya S. and Van Hemert, Otto (2008). Understanding the SubprimeMortgage Crisis. Retrieved on December 11, 2009 form

http://ssrn.com/abstract=1020396.

Hoontrakul, Pongsak (2008). Global Financial Crisis and Implications to Thailand: Anex-Bankers View. Retrieved on November 24, 2009, fromwww.srn.com/abstract=1303358.

Kaminsky, G., Lizondo, S., and Reinhart, C. (1998). Leading indicators of CurrencyCrises. IMF Staff Papers, 45, 148.

Kenourgios, Dimitris Aristeidis, Samitas and Nikos, Paltalidis (2008). Financial Crisesand Contagion: Evidence for BRIC Stock Markets. Retrieved on November 24, 2009

from http://ssrn.com/abstract=1087282.

King, M. and Wadhwani, S. (1990). Transmission of Volatility between Stock Markets.Review of Financial Studies, 3, 533.

Krugman, P. (1979). A model of Balance of Payment Crisis. Journal of Money, Credit,and Banking, 11, 311325.

Kyle, A., and Xiong, W., (2001). Contagion as a Wealth Effect. Journal of Finance, 56,14011440.

Mohan, Rakesh (2008). Global Financial Crisis and Key Risks: Impact on India and Asia.Retrieved on November 24, 2009, from

http://rbidocs.rbi.org.in/rdocs/Speeches/PDFs/87784.pdf

Park, Y., and Lee, J. (2003). Recovery and Sustainability in East Asia, in: ManagingCurrency Crises in Emerging Markets, Dooley M. and J. Frankel (Eds.), University of

Chicago Press, 275320.

Pasquariello, P. (2008). The Anatomy of Financial Crises: Evidence from the EmergingADR Market. Retrieved on December 5, 2009 from

http://webuser.bus.umich.edu/ppasquar/adr.pdf. Pasquariello, P., 2007. Imperfect Competition, Information Heterogeneity, and Financial

Contagion. Review of Financial Studies 20, 391426.
http://ssrn.com/abstract=1020396http://ssrn.com/abstract=1020396http://www.srn.com/abstract=http://ssrn.com/abstract=1087282http://rbidocs.rbi.org.in/rdocs/Speeches/PDFs/87784.pdfhttp://rbidocs.rbi.org.in/rdocs/Speeches/PDFs/87784.pdfhttp://rbidocs.rbi.org.in/rdocs/Speeches/PDFs/87784.pdfhttp://ssrn.com/abstract=1087282http://www.srn.com/abstract=http://ssrn.com/abstract=1020396

Documents

The Anatomy of Financial Crisis