Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model

The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia, India, China and South Africa) countries, as a proxy for the measurement of volatility. Results from the conditional heteroskedasticity long memory model show the evidence of long memory in the squared stock returns of all 35 stock indices studied. Empirical findings show the evidence of contagion during the global financial crisis (GFC) and Euro Zone crisis (EZC). The intensity of contagion varies depending on its sources. This implies that the effects of shocks are not symmetric and may have led to some structural changes. The effect of contagion is also studied by decomposing the level series into explained and unexplained behaviors.

[1]  Jose E. Gomez-Gonzalez,et al.  Stock market volatility spillovers: Evidence for Latin America , 2016 .

[2]  F. Breidt,et al.  The detection and estimation of long memory in stochastic volatility , 1998 .

[3]  Seong‐Min Yoon,et al.  Long memory properties in return and volatility: Evidence from the Korean stock market , 2007 .

[4]  The Effect of Long Memory in Volatility on Stock Market Fluctuations , 2007 .

[5]  Multivariate Fractionally Integrated APARCH Modeling of Stock Market Volatility: A multi-country study , 2011 .

[6]  P. Silvapulle,et al.  LONG-TERM MEMORY IN STOCK MARKET RETURNS: INTERNATIONAL EVIDENCE , 2001 .

[7]  Equity market contagion during global financial and Eurozone crises: Evidence from a dynamic correlation analysis , 2016 .

[8]  A. M. M. Shahiduzzaman Quoreshi,et al.  A long-memory integer-valued time series model, INARFIMA, for financial application , 2014 .

[9]  Marcello Pericoli,et al.  Some Contagion, Some Interdependence: More Pitfalls in Tests of Financial Contagion , 2002 .

[10]  Nicola Spagnolo,et al.  Testing For Contagion: A Conditional Correlation Analysis , 2005 .

[11]  Jonathan H. Wright Long Memory in Emerging Market Stock Returns , 1999 .

[12]  C. Granger,et al.  A long memory property of stock market returns and a new model , 1993 .

[13]  Robert F. Engle,et al.  The Reviewof Economicsand Statistics , 1999 .

[14]  Pilar Grau-Carles Empirical evidence of long-range correlations in stock returns , 2000 .

[15]  Craig Hiemstra,et al.  Another look at long memory in common stock returns , 1997 .

[16]  Carmen M. Reinhart,et al.  Capital Flows to Latin America: Is There Evidence of Contagion Effects? , 1996 .

[17]  J. Geweke,et al.  THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS , 1983 .

[18]  Norman R. Swanson,et al.  An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series , 2006 .

[19]  M. King,et al.  Transmission of Volatility between Stock Markets , 1989 .

[20]  G. Booth,et al.  Are There Long Cycles in Common Stock Returns , 1988 .

[21]  Kurt Brännäs,et al.  Estimation in integer‐valued moving average models , 2001 .

[22]  Johan Lyhagen,et al.  Short and Long Run Dependence in Swedish Stock Returns , 1996 .

[23]  Stavros Degiannakis * Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model , 2004 .

[24]  C. Granger,et al.  Varieties of long memory models , 1996 .

[25]  C. Granger Long memory relationships and the aggregation of dynamic models , 1980 .

[26]  Cheng-Few Lee,et al.  Stock Returns and Volatility on China's Stock Markets , 2001 .

[27]  Sang Bin Lee,et al.  DOES THE OCTOBER 1987 CRASH STRENGTHEN THE CO‐MOVEMENTS AMONG NATIONAL STOCK MARKETS? , 1993 .

[28]  Yonghong Jiang,et al.  The Financial Crisis and Co-Movement of Global Stock Markets—A Case of Six Major Economies , 2017 .

[29]  F. Diebold,et al.  Long Memory and Regime Switching , 2000 .

[30]  Gabriel J. Power,et al.  Long-range dependence in the volatility of commodity futures prices: Wavelet-based evidence , 2010 .

[31]  C. Aloui,et al.  Long-Range Dependence in Daily Volatility on Tunisian Stock Market , 2005 .

[32]  R. Rigobón,et al.  No Contagion, Only Interdependence: Measuring Stock Market Comovements , 2002 .

[33]  R. Baillie,et al.  Fractionally integrated generalized autoregressive conditional heteroskedasticity , 1996 .

[34]  Lumengo Bonga‐Bonga Uncovering equity market contagion among BRICS countries: An application of the multivariate GARCH model , 2017 .

[35]  C. Granger,et al.  AN INTRODUCTION TO LONG‐MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING , 1980 .

[36]  Siem Jan Koopman,et al.  The stochastic volatility in mean model: empirical evidence from international stock markets , 2002 .

[37]  Is Long Memory a Property of Thin Stock Markets? International Evidence Using Arab Countries , 2003 .

[38]  Sabur Mollah,et al.  Conditional Heteroskedasticity in Long Memory Model 'FIMACH' for Return Volatilities in BRICS Equity Markets , 2015 .

[39]  Chi Xie,et al.  Stock market contagion during the global financial crisis: A multiscale approach , 2017 .

[40]  I. Goldfajn,et al.  Financial Market Contagion in the Asian Crisis , 1998, IMF Staff Papers.

[41]  B. Ray,et al.  Long-range Dependence in Daily Stock Volatilities , 2000 .

[42]  E. Ruiz,et al.  Estimation Methods for Stochastic Volatility Models: A Survey , 2004 .

[43]  B. Jeon,et al.  Dynamic correlation analysis of financial contagion: Evidence from Asian markets , 2007 .

[44]  Walter Willinger,et al.  Stock market prices and long-range dependence , 1999, Finance Stochastics.

[45]  M. T. Greene,et al.  Long-term dependence in common stock returns , 1977 .