This paper proposes a new approach to evaluate contagion in financial markets. Our measure of contagion captures the co-incidence of extreme return shocks across countries within a region and across regions that cannot be explained by linear propagation models of shocks. We characterize the extent of contagion, its economic significance, and its determinants using a multinomial logistic regression model. Applying our approach to daily returns of emerging markets during the 1990s, we find that contagion, when measured by the co-incidence within and across regions of extreme return shocks, is predictable and depends on regional interest rates, exchange rate changes, and conditional stock return volatility. Evidence that contagion is stronger for extreme negative returns than for extreme positive returns is mixed.
*Published:
Kee-Hong Bae & G. Andrew Karolyi & Rene M. Stulz, 2001. "A new approach to measuring financial contagion," Proceedings, Federal Reserve Bank of Chicago, issue May, pages 489-529.
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