Revisiting calendar anomalies in Asian stock markets using a stochastic dominance approach

Abstract

Extensive evidence on the prevalence of calendar effects suggests that there exist abnormal returns. Some recent studies, however, have concluded that calendar effects have largely disappeared. In spite of the non-normal nature of stock returns, most previous studies have employed the mean-variance criterion or CAPM statistics. These methods rely on the normality assumption and depend only on the first two moments to test for calendar effects. A limitation of these approaches is that they miss important information contained in the data such as higher moments. In this paper we use a stochastic dominance (SD) test to test for the existence of day-of-the-week and January effects. We use daily data for 1988-2002 for several Asian markets. Our empirical results support the existence of weekday and monthly seasonality effects in some Asian markets, but suggest that first-order SD for the January effect has largely disappeared. © 2006 Elsevier B.V. All rights reserved.