Does average skewness matter in Singapore?

Abstract

This paper investigates whether average skewness can predict future market excess returns in the Singapore stock market. Motivated by Jondeau et al. (2019), who initially established such a relationship in the U.S. market, and subsequent replications by Li et al. (2020) for Taiwan and Annaert et al. (2023) for Europe, this paper adopts a similar regression framework to test for predictive power in a different market context. Using both value-weighted and equal-weighted measures of average skewness and variance, and correcting for heteroskedasticity and autocorrelation with Newey-West standard errors, we find no significant relationship between skewness and next-month returns. Unlike the Taiwan study, we also find no significance in the two-month horizon, suggesting that the delayed correction observed in retail-driven markets may not apply in Singapore. We argue that this result is not solely methodological, but reflects deeper structural characteristics of Singapore’s capital market. Despite Singapore’s emergence as a leading financial hub, this does not translate to its equity market, which has low listing activity, weak trading volume and persistent delisting. These conditions hinder cross-sectional dispersion and mispricing, reducing conditions under which skewness may have predictive value. These findings contribute to the growing literature on cross-market return predictability and challenge the generalisability of skewness-based forecasting models across different financial environments.