The Impact of Major Event on Regime Switching of Financial Market Volatility Spillover: The Case of the 2011 Japanese Ea
Natural disasters may inflict significant regime switching of financial market volatility spillover. Using Japan and other four world’s major stock market indexes, this chapter examines if any regime switching occurred across financial markets after the 2
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The Impact of Major Event on Regime Switching of Financial Market Volatility Spillover: The Case of the 2011 Japanese Earthquake Lu Wang, Jiong-lou Xu, and Mao Li
Abstract Natural disasters may inflict significant regime switching of financial market volatility spillover. Using Japan and other four world’s major stock market indexes, this chapter examines if any regime switching occurred across financial markets after the 2011 Japanese earthquake based on copula model. The results indicate that strengthened cross-markets regime switching with significant evidence of volatility spillover are noticeable for Japan-Hong Kong, Japan-US and JapanChina pairs. Every national/regional stock market is found to suffer on the effect by the 2011 Japanese earthquake. Keywords Copula • major event • regime switching • volatility spillover
62.1 Introduction The study of volatility spillover among international financial markets has attracted the interest of researchers and professionals both in theoretical and empirical field (King et al. 1994; Diebold and Yilmaz 2009; Malik and Ewing 2009). Aiming to control risks they face, portfolio managers and regulators need to take into account the volatility spillover of assets in the international financial markets, for example. A volatility spillover occurs when changes in price volatility in one market produce a lagged impact on volatility in other markets, over and above local effects (Milunovich and Thorp 2006). Volatility spillover patterns appear to be widespread in financial markets. There is significant evidence for spillovers between equity markets, futures contracts, bond markets, equities and exchange rates, exchange rates, various industries, commodities, size-sorted portfolios, and swaps.
L. Wang () • J. Xu • M. Li Department of Statistics, Southwest Jiaotong University, Chengdu, China e-mail: [email protected] E. Qi et al. (eds.), The 19th International Conference on Industrial Engineering and Engineering Management, DOI 10.1007/978-3-642-37270-4 62, © Springer-Verlag Berlin Heidelberg 2013
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Macroeconomic policy makers and investors are not only concerned about the existence of the volatility spillover but even more about sudden breaks in volatility spillover, for example the breaks caused by currency crises. Such breaks could affect the economy through a change in capital flows or in real linkages among markets, such as trade. They may lower diversification benefits from international investing and change investors’ behavior after the break (Hitt and Hoskisson 1994; Forbes and Rigobon 2002; Ang and Bekaert 2002). Just as the normal distribution is inadequate for modeling univariate time series, so the bivariate normal distribution is not suitable for modeling the relationship between two assets (Li 2000). As well as the asset returns not being normally distributed, their comovements may not be adequately captured by correlation coefficients. For example, marginal distributions tend to be characterized by fat tails and the probability of
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