As emerging economic systems aspire to go truly modern and developed states, one of the cardinal challenges these states face is to turn to the issue of heavy dependance on mature economic systems. Advancement towards self-dependence is typically measured by analyzing assortment of indexs such as macroeconomic integrating, stock market correlativities, concern rhythms synchronism, etc. The recent planetary economic crisis and ongoing Eurozone convulsion have one time once more revived the involvement of research workers and policy shapers to look into emerging economic systems with respect to their autonomy and decoupling potencies. The latest Global Competitiveness Report ( 2012-2013 ) acknowledges the impact of these crises on emerging states. Due to fragile recovery of USA and troubled European states, World Economic Outlook ( IMF, 2012 ) besides reports the underperformance of emerging economic systems in footings of accomplishing economic growing in 2012 compared to old twelvemonth. As a effect, the glooming economic mentality of emerging markets has caught the attending of regulators and investors to analyze their dynamic relationship with developed states. In this visible radiation, the present survey efforts to analyze the stock market correlativities between emerging and mature markets peculiarly the five most vulnerable states of Euroarea popularly leveled as GIPSI ( Greece, Ireland, Portugal, Spain and Italy ) . By emerging states, we imply an acronym which is considered as the hub of investing and portfolio variegation and sometimes treated as individual homogeneous fiscal plus category in the universe, popularly leveled as “ BRIICKS ” . BRIICKS is a pool of seven economic systems viz. , Brazil, Russia, India, Indonesia, China, South Korea and South Africa. The initial version of this acronym was coined by Goldman Sachs as ‘BRIC ‘ which subsequently extended by including Indonesia and South Korea in 2010 ( see Global Development Horizon, 2011, World Bank ) . South Africa is included in 2011. However, the late concluded meeting of BRICS held in New Delhi, India, doesnot figures the name South Korea and Indonesia in the acronym. But in our survey, we carry out the empirical analysis on the drawn-out version of BRIICKS including two excluded economic systems due to their strong economic and trade dealingss with other emerging markets. The analysis of cross market correlativities is of great significance for cross-country optimum portfolio allotment and hazard direction. Several surveies have examined the procedure of time-varying cross-market correlativities particularly at the clip when the economic system is wholly in the clasp of downswing caused by the rapid transmittal of daze arising from neighbouring or far distant state ( see for example, Kim et al. , 2005 ; Phylaktis and Ravazzolo, 2005 ; Cappiello et al. , 2006 ; Chiang et al. , 2007 ; Dooley and Hutchison, 2009 ; Kenourgios et al. , 2011 ; Aloui et al. , 2011 ; Marcal et al. , 2011 ; Samarakoon, 2011 ) .

The burgeoning literature on fiscal contagious disease indicates that the stock markets in crisis-hit states usually indicate higher degrees of mutuality, ensuing in speedy spread of fiscal dazes across markets within a short span of clip. A important addition in stock returns correlativities during the crisis period is referred as contagious disease which in general term defined as the spread of fiscal dazes from one state to others ( see for example, Lessard, 1973 ; Solnik, 1974 ; Ang and Bekaert, 1999 ; Longin and Solnik, 1995 and 2001 ; Chiang et al. , 2007 ; Dooley and Hutchison, 2009 ; Syllignakis and Kouretas, 2011 etc. ) . The probe of fiscal contagious disease is of great significance because of its detrimental impacts on planetary economic system in dealingss to the strategic plus allotment, preparation of pecuniary every bit good as financial policy ; plus pricing and fiscal hazard direction ( see Kaminsky and Reinhardt, 1999 ; Forbes and Rigobon, 2002 ; Longstaff, 2010, among others ) . In recent old ages, in aftermath of recent US subprime and subsequent Eurozone perturbation, the scrutiny of fiscal contagious disease across economic systems has become a greatly focussed country of research.

In this survey, we concentrate on Eurozone debt crisis ( 2009-2010 ) by analyzing the fiscal contagious disease for BRIICKS economic systems by sing GIPSI states as a beginning of contagious disease along with USA, UK as planetary and Japan as a regional factor. We besides construct a GIPSI Crisis Index ( henceforth, GCI ) utilizing GIPSI ‘s stock market returns in order to reconfirm the grounds of contagious disease on BRIICKS markets. Our survey doesnot cover the US subprime and earlier crises periods which have already been undertaken by a big figure of surveies ( see for inside informations, Kenourgios et al. , 2011 ; Samarakoon, 2011 ; Kenourgios and Padhi, 2012 ) .

The Euroarea crisis is by and large considered as a by-product of US subprime owing to its strong contagious disease effects on Eurozone economic systems peculiarly on GIPSI states, taking to eroding of investor assurance at an unprecedented degree. The spread of contagious disease started with Greece due to strong likeliness of default on its autonomous debt duty in late 2009 and all of a sudden gripped the full Europe and other economic systems across Earth. It is noteworthy that though the crisis in GIPSI states is the consequence of autonomous debt hazard and non wholly originated from stock market but the spread of such hazard has majorly been realized with strong and relentless autumn in stock market monetary values across accomplished states. Therefore, one of the aims of this survey is to analyze the contagious disease effects by analysing dynamic conditional correlativities between GIPSI and BRIICKS stock markets.

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Eurozone crisis ( 2010 ) can loosely be divided into two classs. First, a banking crisis which was an result of strong fiscal linkages with US Bankss and prostration of belongings markets in some EU states and ( two ) due to sovereign debt crisis linked with rising authorities shortages and debt degrees over many old ages that was against the rules laid down in the Maastricht Treaty ( see Blundell-Wignall and Patrick, 2011 ) . Consequently, Ireland and Greece economic systems saw their economic systems on the brink of debt default which is besides the instance for Portugal, Spain and Italy.

2. Brief Literature Review

After a series of economic and fiscal crises observed during 1998-2002, there have been uninterrupted attempts made by research workers to analyze the different channels of contagious disease.[ 1 ]Most old work on contagious disease focused chiefly on mature markets instead than emerging markets. Due to the above mentioned features, more and more research on emerging markets has been conducted with an accent on the cross-market correlativities particularly at the clip of downswing ( see for illustration, Hamao et al. , 1990 ; Theodossiou and Lee, 1993 ; Bekaert, 1995 ; Bekaert and Harvey, 1995 ; Meric and Meric, 1997 ; Goetzmann et al. , 2001 ; Chen et al. , 2002 ; Yang, 2005 ; Cappiello et al. , 2006 ; Chiang et al. , 2007 ; Dooley and Hutchison, 2009 ; Kenourgios et al. , 2011 ; Marcal, et al. , 2011 ; Samarakoon, 2011 ; Min and Hwang, 2012 ; Choe et al. , 2012 ; Kenourgios and Padhi, 2012 ; Suardi, 2012 ) . Even though most of the aforesaid surveies have focused on emerging markets in Asia, Latin America and assorted of planetary markets. There is a limited literature on the stock market linkages in emerging markets peculiarly on the basket of states such as BRIICKS. Few surveies have besides examined the impact of US subprime on emerging markets. Dooley and Hutchison ( 2009 ) examine the likeliness of uncoupling by emerging markets. Their survey reports the grounds of uncoupling before the crisis period and re-coupling during the crisis period. Using asymmetric DCC-GARCH theoretical account, Yiu et al. , ( 2010 ) examine the kineticss of cross market correlativities among 11 stock markets ( viz. , Australia, China, Hong Kong, Indonesia, Japan, Korea, Malaysia, New Zealand, Philippines, Singapore and Thailand ) . Their survey finds strong grounds of contagious disease from USA to Asiatic markets in 2007, while, they report no grounds of contagious disease between USA and Asiatic markets during Asiatic crisis period. Aloui et Al. ( 2011 ) analyze the stock markets of BRIC states along with USA. Using copula attack for the sample period of 2004 to 2009, they find that there is significantly high degree of time-varying correlativity and continuity ( during bull and bear markets ) between each of the BRIC and USA markets. Samarakoon, ( 2011 ) provides the grounds of transmittal of US fiscal crisis dazes to emerging and frontier markets ( including European and non-European ) . The survey reports the mutuality and contagious disease between US and emerging markets whereas frontier markets as contagious. While, re-examining the grounds of contagious disease based on changeless correlativity trial during Asiatic crisis ( 1997 ) on big basket of states, Choe et al. , ( 2012 ) utilizing structural dynamic conditional correlativity ( SDCC-GARCH ) theoretical account, found no grounds of contagious disease for sample states. Kenourgios et al. , ( 2011 ) examined the BRIC markets for the period 1995-2006. The survey analysed all crisis periods occurred before 2002. Their survey reported the contagious disease effects from crisis state to other examined markets for each of the economic crises periods. Kenourgios and Padhi ( 2012 ) examined several crisis periods viz. , Asian, Russian and Argentinean crises and planetary fiscal crisis of ( 2008 ) . Using the information of equity and bond markets, the survey finds the grounds of fiscal contagious disease during Asiatic and Russian crises. While, the contagious disease consequence of Argentinean crisis was limited on emerging markets. Suardi ( 2012 ) analysed the impact of planetary fiscal crisis utilizing the four most popular market indices viz. , Emerging Markets Latin America, Emerging Markets, Emerging Markets Asia, and the World in order to analyse the impact of subprime on emerging markets. The survey studies strong impact of US born crisis on mature and emerging markets. Based on the above mentioned surveies, it can be inferred that most of the surveies have analysed the contagious disease effects of assorted crises on emerging and mature markets but none of the survey covers the recent European economic crisis ( 2010 ) on emerging markets. On methodological forepart, though there is sufficient literature on the application of conventional clip series theoretical accounts such as cointegration, causality and Vector Auto Regression ( VAR ) , but the application of modern-day volatility theoretical accounts has merely been popular in recent surveies every bit far as the analysis of fiscal contagious disease is concerned. The present survey makes a figure of parts to the relevant literature. First, to the best of our cognition this is the first survey that examines the issue of fiscal contagious disease for an drawn-out version of acronym BRICs as BRIICKS, look intoing the contagious disease effects of Eurozone crisis 2009-2012. Second, we extend our analysis to a big set of emerging markets with significant diverseness by sing GIPSI as beginning of contagious disease, UK and USA economic systems as planetary and Japan as regional factor. Third, we employ the Dynamic Conditional Correlation ( DCC ) multivariate GARCH theoretical account developed by Engle ( 2002 ) to look into the form of short-term mutuality and analyze possible channels of contagious disease effects between GIPSI, Japan, UK and USA and BRIICKS markets. A concluding novel characteristic of this survey is the thorough analysis of the possible policy deductions that takes into history the alterations in the correlativity patterns across states and clip. The remainder of the paper is organized as follows. Section 3 presents the informations employed and discusses research methodological analysis every bit good as empirical consequences and Section 4 terminals with decision and treatment.

3. Research Methodology and Empirical Results

The informations used in this paper is day-to-day stock-price indices from February 02, 1996, through January 31, 2012, for the equity markets of seven BRIICKS states. It may be noted that due to absence of informations, the sample period of Italy starts from June 03, 2003 to January 31, 2012. For stable period appraisal, in instance of Italy, the sample period of each state is adjusted consequently. The information set consisted of the stock market indices of Brazil, Russia, India, Indonesia, China, South Korea and South Africa. The stock market indices of GIPSI states along with UK and USA are considered as planetary and Japan as regional factor for BRIICKS states. All stock-price indices are used in dollar currency footings and are based on day-to-day shutting monetary values for each market.[ 2 ]The stock market indices are transformed into day-to-day rates of returns taking the first difference of the natural log of each stock-price index multiplied by 100. The beginning of the information is DataStream International.

Since the aim of present survey is to analyze the impacts of GIPSI stock market returns on BRIICKS, by manner of comparing the DCC correlativities during crisis and stable period. We spilt the sample period as follows: ( 1 ) . Eurozone crisis period, ( May 2009 to January 2012 ) . The period choice is in line with Missio and Watzka, ( 2011 ) . ( 2 ) . Stable period is taken to be February 1996 to July 2007. The stable period takes into history before and after the existent clang utilizing all historical information contained in pre and post-crash informations ( see Kenourgios, Samitas and Paltalidis, 2011 ) . Stable period doesnot take into history the convulsion periods of Asiatic crisis ( 1997 ) , Brazilian crisis ( 1998 ) , Dot Com bubble flop ( 2000 ) , Argentine crisis ( 2002 ) and the periods of Subprime crisis ( 2007-2009 ) .

[ Insert Table 1 here ]

We begin the analysis of empirical consequences with full sample statistics ( including both stable and crisis period ) followed by the descriptive statistics of merely sample crisis period. This is chiefly to analyze the differences in behavior of conventionalized facts of both the sample periods. Table 1 ( Panel A ) shows the descriptive statistics of full sample. The highest average day-to-day returns is observed in instance of Russia ( 0.080 % ) followed by BRZ ( 0.053 % ) , CHINA ( 0.044 % ) and IND ( 0.038 % ) . The market with last day-to-day stock market returns is observed in SKOR ( 0.013 % ) . While, during crisis period ( see Table 1, Panel B ) , it ‘s noteworthy that unlike full sample statistics in which the returns of GIPSI states are positive except GRC, in the Eurozone crisis period these markets exhibit negative returns with the exclusion of IRLD. During crisis period, the highest mean returns are reported for INDO ( 0.113 % ) followed by Russia ( 0.086 % ) , SAF ( 0.074 % ) , BRZ ( 0.071 % ) and SKOR ( 0.065 % ) . The lowest mean returns is in instance of China ( -0.004 % ) with IND making comparatively better, demoing the returns of ( 0.050 % ) . Equally far as volatility is concerned, among BRIICKS states, the highest volatility during full sample period is observed in instance of Russia ( 2.892 % ) and lowest in China ( 1.765 % ) . While, during crisis period, the highest standard divergence is reported for Russia ( 2.015 % ) followed by SAF ( 1.873 % ) , SKOR ( 1.851 % ) and IND ( 1.780 % ) . During both the sample periods, as expected the lopsidedness for each series is negative ( with the exclusion of IND, SKOR ) and leptokurtic for BRIICKS states which can be explained by the series of market recessions over the survey period and has besides substantiated the crisis period. It is non surprising that the Jarque-Bera ( JB ) trial indicates that all stock market returns are non-normal. We besides report the Ljung-Box ( LB ) statistic up to ten orders in degrees and squared of returns for both examined samples. The consequences clearly indicate that there is consecutive correlativity in degrees during full sample period with the exclusion of SAF and SPAIN. While, during crisis period there is no consecutive correlativity at degrees with the exclusion of USA. All variables exhibit the consecutive correlativity in both samples in squared footings, proposing the being of the volatility constellating associated with ARCH procedure in these series. Based on the illation obtained from descriptive statistics, it can be inferred that there is limited impact of Eurozone crisis on examined emerging markets compared to planetary fiscal crisis ( 2008 ) . We shall farther reconfirm this by analyzing the cross market correlativities as discussed in following sub-section.

3.1. The DCC theoretical account and appraisal consequences

Table 2 ( Panel-A ) presents the consequences of the multivariate DCC-GARCH theoretical account between GIPSI and BRIICKS stock markets. The impact of stock market of GIPSI states on BRIICKS markets as shown by ( I?2 ) in equation ( 1 ) is extremely important with positive co-efficient, connoting the strong effects of GIPSI stock markets on BRIICKS. The degree of significance of the AR ( 1 ) term in the average equation, ( I?1 ) is mixed for most of the GIPSI states. The estimated consequences of DCC ( 1, 1 ) parametric quantities ( a+b ) as in equation ( 3 ) exhibit that both the parametric quantities in instance of all sampled states are extremely important, connoting a significant time-varying co-movement. Furthermore, the degree of continuity exhibited by conditional correlativities is assorted with the mean amount of the two coefficients runing from 0.147 to 0.864 during the sample period. The lowest volatility continuity is observed in instance of IRLD and JAPAN. Furthermore, it is shown that the coefficients for the lagged conditional volatility and Iµ2 footings in the discrepancy equation are extremely important, warranting the rightness of the GARCH ( 1, 1 ) specification. Similarly, DCC-GARCH consequences of Japan ( regional factor ) and USA and UK ( planetary factor ) as shown in ( Panel F, G & A ; H ) indicate the impact of stock markets of these economic systems on BRIICKS with the exclusion of INDO, as exhibited by the co-efficient of ( I?2 ) . We besides evaluate the GARCH theoretical account estimated for each series. All parametric quantities seem to suitably fulfill the standards of GARCH theoretical account choice with the degree of continuity runing from 0.72 to 0.99 with the exclusion of BRZ.

Several surveies have used the pairwise conditional correlativities to exhibit the contagious disease effects during periods of fiscal convulsion. Boyer et. al. , ( 2006 ) name contagious disease a phenomenon which can either be investor induced through portfolio rebalancing or cardinal based. The latter can be associated with what has been described by Forbes and Rigobon ( 2002 ) as mutuality, while the former instance is described in behavioural finance literature as herding. Herding majorly occurs when a pool of investors starts following other investors, and has been defined as the “ convergence of behaviours ” ( see for example, Hirshleifer and Teoh ( 2003 ) . Some recent empirical surveies ( see Corsetti et al. , 2005 ; Bekaert and Harvey, 2000 ; Jeon and Moffett, 2010 ; Syllignakis and Kouretas, 2011 ; Suardi, 2012 ) used the dynamic conditional correlativities step to look into possible crowding behaviour every bit good as contagious disease effects on emerging fiscal markets during examined crises period.

[ Insert Table 2 here ]

We now move to analyse the estimated conditional correlativity coefficients. In Table 3, we exhibit the mean conditional correlativities between GIPSI with Japan, UK and USA and BRIICKS stock markets. In add-on, the crisis period correlativity consequences are farther compared with stable period. Among all GIPSI markets, compared to stable period correlativity, IRLD shows highest correlativity with BRIICKS stock markets during the crisis period followed by SPAIN, PORT, GRC and ITALY. Among BRIICKS states, the stock market of SAF exhibits high and important correlativity with GIPSI markets followed by Russia, India, INDO, SKOR and China. The lowest correlativities are reported for BRZ which besides exhibits negative correlativity with GRC, connoting a decoupling consequence. Therefore, it is inferred that the stock markets of IRLD, SPAIN and PORT are holding stronger contagious disease effects on BRIICKS markets compared to GRC whose impact seems to hold been overemphasized in recent crisis argument and literature. Sing planetary ( USA and UK ) and regional ( Japan ) factors, the correlativity consequences indicate that UK appears to be most contagious state followed by USA for BRIICKS markets. The consequences imply that due to strong fiscal linkages, the stock market of UK still plays important function in emerging markets compared to USA.

[ Insert Table 3 here ]

3.2. Time-varying Cross Market Co-movements

In this subdivision, we analyze the time-varying cross market correlativities for sample states. In the literature, the surveies of Connolly et al. , ( 2007 ) , Aydemir ( 2008 ) and Cai et al. , ( 2009 ) have provided the grounds of stronger international market linkages when the degree of hazard is higher. For this, we estimated the undermentioned equation

Where, is the estimated pair-wise conditional correlativity co-efficient between the stock market returns of the GIPSI/USA/UK/Japan and BRIICKS stock markets, such that i= GIPSI/USA/UK/Japan and j=BRIICKS stock markets. is the conditional volatility of each of BRIICKS states and is the conditional volatility of GIPSI/USA/UK/Japan states. The consequences are shown in Table 4. The mark ofcoefficients varies across markets in BRIICKS. In instance of GRC, all the coefficients are positive and important. A positive suggests that conditional correlativities between the GRC and BRIICKS market rise with the volatility of the GRC market and vice-versa. The consequences have strong deductions for investors in doing variegation schemes particularly when the stock market returns of GIPSI and USA/UK/Japan markets are above norm. In instance of GIPSI markets, the coefficients are all positive and important with the exclusion of SAF and IND in instance of IRLD ; IND and SKOR in instance of PORT and INDO, SKOR and RUSSIA in instance of Spain.

For Japan, USA and UK, all BRIICKS stock markets exhibit positive relationship connoting that BRIICKS markets are positively linked with these markets. Furthermore, the explanatory power of arrested development consequences is besides high ( Adjusted R2 ) . In instance of GIPSI, it ranges from 0.312 % to 0.840 % . Similarly for Japan, USA and UK, Adj.R2 is comparatively high and ranges from 0.138 % to 0.724 % .

[ Insert Table 4 here ]

3.3. GIPSI Crisis Index and BRIICKS Markets

Following, we construct a GIPSI Crisis Index ( GCI ) based on the stock market returns of five GIPSI states.[ 3 ]This is chiefly to analyze the combined effects of GIPSI states on BRIICKS stock markets. The consequences, shown in Table 5 ( Panel A ) , indicate that the consequence of GCI on BRIICKS stock markets are extremely important and systematically of big magnitude, corroborating the influential function of the GIPSI states on the BRIICKS stock markets. The DCC-GARCH ( 1, 1 ) parametric quantities ( a+b ) are high important. While, analyzing the cross market co-movements, the consequences indicate that the mean conditional correlativity of GCI ranges from 0.104 and 0.761, connoting that the combined effects of GCI states on BRIICKS markets is stronger than their single effects. It may be pointed out that the most vulnerable state is SAF ( 0.761 ) followed by Russia ( 0.635 ) , IND ( 0.415 ) and INDO ( 0.291 ) while least wedged are China ( 0.177 ) and Brazil ( 0.104 ) . The GCI consequences re-confirm our findings associating to single GIPSI states.

[ Insert Table 5 here ]

The cross market co-movement arrested development consequences as shown in equation ( 4 ) indicate that thecoefficients in instance of BRIICKS are important and positive, connoting that the conditional volatility of GIPSI market drives the correlativity between GIPSI and BRIICKS markets ( see Table 6 ) . The Adj.R2 of arrested development consequences are higher and ranges from 0.892 to 0.986, confirming the fact that BRIICKS states are strongly linked with GIPSI states. The highest cross market co motion is observed for SAF while the really low cross market correlativities is reported for IND and BRZ. From the empirical consequences, it appears that BRZ, IND and SKOR seem to be most coveted stock markets for US and foreign investors in the presence of Eurozone crisis.

[ Insert Table 6 here ]

4. Decision and treatment

This paper examines fiscal contagious disease in an emerging market scene by manner of look intoing the impact of GIPSI stock markets along with USA, UK and Japan on BRIICKS stock markets. Using multivariate DCC-GARCH theoretical account, the consequences indicate important fluctuation in conditional correlativities during Eurozone crisis period ( May 2009-January 2012 ) . The analysis of dynamic conditional correlativity provides significant grounds on the being of contagious disease effects due to crowding behavior in the stock markets of BRIICKS. The empirical consequences elucidate the being of fiscal contagious disease of GIPSI on BRIICKS stock markets, connoting that the later is extremely prone to contagious disease. Further, the combined effects of GIPSI markets on BRIICKS stock markets are stronger than any of their standalone effects. Analyzing the Euro-zone crisis period ( 2009-2012 ) , the empirical consequences indicate that among GIPSI states, IRLD, SPAIN and PORT appear to be most contagious for BRIICKS markets compared to Greece. Among BRIICKS markets, BRZ, IND and SKOR seem to be most desirable stock markets for international investors during the examined crisis period. The survey reports several deductions on the demand to construct an international fiscal architecture that will assist the emerging market economic systems to minimise the contagious disease hazard in future. In order to recognize this, it is needed that the BRIICKS market should advance policy research and international co-ordination. Constitution of pool of financess or a bank peculiarly for emerging markets will besides assist BRIICKS markets in minimising the detrimental deductions of contagious disease effects. Creation of Sovereign Wealth Funds ( SWFs ) will besides play an of import function in guaranting high economic growing and stock market stabilisation for emerging markets

The survey has strong deductions for cross-country investings, as the portfolio variegation benefits of puting in these emerging markets appear to be small low when it is most desirable for them to be high, that is, in the crisis period. From policy shapers ‘ position, the findings of the survey provide usefull deductions about the preparations of possible uncoupling schemes to insulate the economic system from contagious effects. For many-sided administrations like International Monetary Fund ( IMF ) and World Bank, the survey will supply of import way in set abouting coordinated deliverance steps for vulnerable every bit good as contagious states. The survey contributes to fiscal contagious disease literature for emerging markets and is relevant peculiarly in the visible radiation of current Eurozone crisis.


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