Events that Shook the Market: An Insight from Nonlinear Serial Dependencies in Intraday Returns

Abstract

The present study proposes the use of nonlinear serial dependencies in the returns series for assessing market responses to new information. Unlike the standard event study methodology, this paper advocates a reserve form that let data analysis to first detect those periods with significant nonlinearity, and then identify whether their occurrences can be associated with major economic or political events. Our proposed research framework involves the application of the Hinich (1996) portmanteau bicorrelation test statistic in a moving time windows setting. Using the Malaysian stock market as a case study, our empirical application is able to detect not only the presence of nonlinear serial dependencies in the KLCI intraday ten-minute returns, but also the time periods when they occurred. The next stage of event-matching managed to identify major events that unsettled the local stock market in all cases except one. In particular, the Russian crisis, the unorthodox capital control measures and the Brazilian crisis are found to be responsible for the short burst of nonlinear behavior. However, the paper noted that factors that shook the market need not be news announcement in the media. It could be due to, among others, rumors, speculations, expectations, or worries prevail in the investment communities.