Abstract

AbstractThis paper empirically explores dynamic risk impact of extreme volatility between stock and foreign exchange markets in emerging markets. Based on CoVaR analysis, we construct networks to investigate the nonlinear and dynamic evolution characteristics of risk contagion. The results show that stock and foreign exchange markets exhibit asymmetric tail dependence. All networks present small world network characteristics. The risk tolerance impact is more noticeable than risk overflow and stock markets are more sensitive to risk contagion. In the minimum spanning tree (MST), Korean stock market and foreign exchange markets of India and China are critical nodes in the minimum path of risk overflow.

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