A new analytical approach for identifying market contagion

Abstract

This study proposed a new analytical approach to identify the excessive comovement of two markets as contagion. This goal is achieved by linking latent-factor and single-equation error correction models and evaluating the breaks in the short- and long-term relationships and correlatedness in the linked model. The results demonstrated that a short-term relationship representing the market speed ratio between two markets plays a key role in contagion dynamics. When a long-term relationship or correlatedness is broken (comovement change) due to a break in the short-term relationship (market speed ratio), contagion is highly likely and should be formally declared. Bayesian posterior probabilities were calculated to determine the cause. Furthermore, this study applied this analytical Bayesian approach to empirically test the contagion effects of the U.S. stock market during the global financial crisis between 2007 and 2009 using 22 developed equity markets.