Does average skewness matter in Singapore?

• المؤلفون الرئيسيون: See, Gideon Jun Hao, Tan, Gao Jie, Tan, Guang Feng
• مؤلفون آخرون: Tang Yang
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2025
• الموضوعات: Social Sciences; Skewness
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/184428
• المؤسسة: Nanyang Technological University

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.