Russian equity market linkages before and after the 1998 crisis: Evidence from stochastic and regime-switching cointegration tests

Lucey, Brian M.; Voronkova, Svitlana

doi:10.1016/j.jimonfin.2008.07.004

Cited by 64 publications

(26 citation statements)

References 74 publications

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“…In a similar fashion, Zheng and Zuo (2013) adopted a Markov-switching causality approach to model and test the potential instability of volatility transmission among US, UK, German, Japan and Hong Kong markets in tranquil and turmoil periods. Lagoarde-Segot and Lucey (2007) allow for regime switching in analyzing the interdependence of Middle East and North African (MENA) stock markets, and Lucey and Voronkova (2008) for European and Russian stock markets. While, R. Engle, Gallo, and Velucchi (2012) examines East Asian stock markets by introducing two dummy variables for the Asia crisis and the post-crisis periods.…”

Section: Related Literaturementioning

confidence: 99%

Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis

Umer¹,

Coşkun²,

Kiracı³

2018

j.financ.econ.res

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This study investigates the presence of return and volatility spillover across EAGLEs stock markets, namely China, India, Indonesia, Russia, Brazil, Turkey and Mexico. A multivariate GARCH DCC and BEKK frameworks are employed by classifying the total sample (i.e. from January 2002 to February 2017) into three sub-periods according to the 2008 Global financial crisis. The result shows a significant and positive spillover effect among stock markets in the pre-crisis and post-crisis periods. The transmission of spillover from external markets intensely influenced by US stock market. Furthermore, strong inter-connection and channel of spread observed among EAGLEs stock market during the post-crisis period.

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Section: Related Literaturementioning

confidence: 99%

Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis

Umer¹,

Coşkun²,

Kiracı³

2018

j.financ.econ.res

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“…The authors unveiled that this model is more suitable to capture volatility spillovers. Quite similar approach was used by Lucey and Voronkova (2007) for the Russian market. Performing a MGARCH with constant conditional correlation (hereafter, CCC) model, Worthington and Higgs (2004) analyzed the return and the volatility spillovers between some developed and emerging Asian stock markets.…”

Section: Review Of Previous Studiesmentioning

confidence: 99%

Emerging Equity Markets Connectedness, Portfolio Hedging Strategies and Effectiveness

Harrathi¹,

Aloui²,

Houfi³

et al. 2016

International Journal of Financial Research

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In this paper, we investigate the volatility spillovers between equity market indexes for Islamic and non-Islamic emerging countries. To do so, we implement a combination of a vector autoregressive (VAR) and a multivariate GARCH models under BEKK specification (VAR-BEKK-MGARCH) models with constant conditional correlation (CCC) and dynamic conditional correlations (DCC) for daily equity returns of six markets, namely Turkey, Indonesia, Egypt, Mexico, China and Brazil. Our findings disclose strong volatility spillovers among the Islamic and the non-Islamic country' market returns. The volatility spillovers are time varying and are affected by the occurrence of recent financial crises. Furthermore, we extent the volatility spillovers analysis by providing some financial implications in terms of optimal portfolio' allocations and hedging effectiveness. Specifically, we estimate the optimal weights for a minimum risk multi-country portfolios, we compute the hedge ratio and we assess the hedging strategies' effectiveness. Our findings provide prominent implications for policy makers and portfolio managers in terms of the stability of the financial systems, asset allocation decisions and designing portfolio hedging strategies.

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“…8, No. 8;2013 (USA), whereas during post crisis period they are FTSE100 (UK) and Sensex (India) respectively. Similarly a preliminary understanding about cotemporaneous relationship among stock prices is estimated through correlation coefficient.…”

Section: Empirical Analysismentioning

confidence: 99%

“…These mixed evidences pose an important empirical question; are inter-linkage among stock markets time sensitive? In this context, it is worthwhile to mention few noteworthy studies namely Sheng(2000), Cifarelli (2000), Hashmi (2001), Tan (2001), Ratanapakorna (2002), Jang (2002), Yang(2002), Kim (2005), Fan (2003), Melle (2002), Click and Plummer (2005), Lucey and Voronkova(2008) etc. These studies have concentrated on the stock market integration during 1997-1998 Asian financial crises and found that there is shift in the pattern of return and volatility transmission during crisis period.…”

Section: Introductionmentioning

confidence: 99%

Pre & Post-Recession Stock Markets Integration: Some Empirical Evidence

Padhan¹,

Sujit²

2013

IJBM

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The financial markets across globe have become distinctly integrated owing to liberalization and globalsiation policy as well as advancement of information technology. The contagion effect of macroeconomic disturbances or financial crisis, internally and externally, is rapidly disseminating across various economies. The recent global recession of 2007-09 started with US subprime crises and subsequently followed by Lehman brother crisis affected all most all major economies of the world. In this contenxt, the present paper explores the stock market integration of leading stock exchanges across various countries during pre and post economic crisis of 2007-09. Thus for empirical analysis, it uses the data since 2004-2012. It attempts to find out the breaks point, if any, in the pattern of stock price movements endogenously. Further efforts have also been made to examine changing pattern of relationship among stock prices using bivariate and multivariate cointegration techniques. The study suggests that although stock markets are integrated globally, the integration is very weak. This proposes that stock prices as well as returns are not strongly interrelated across markets. The Granger casualty results also provides mixed evidences, although some changes are noticed about the causality between stock prices from pre-recession to post recession period in Chinese stock markets.

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Russian equity market linkages before and after the 1998 crisis: Evidence from stochastic and regime-switching cointegration tests

Cited by 64 publications

References 74 publications

Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis

Time-varying Return and Volatility Spillover among EAGLEs Stock Markets: A Multivariate GARCH Analysis

Emerging Equity Markets Connectedness, Portfolio Hedging Strategies and Effectiveness

Pre & Post-Recession Stock Markets Integration: Some Empirical Evidence

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