Do average higher moments predict aggregate returns in emerging stock markets?

Sumaira Chamadia,Muhammad Kashif,Mobeen Ur Rehman

doi:10.1108/jabes-08-2021-0140

Abstract

PurposeIt has been demonstrated in the US market that expected market excess returns can be predicted using the average higher-order moments of all firms. This study aims to empirically test this theory in emerging markets.Design/methodology/approachTwo measures of average higher moments have been used (equal-weighted and value-weighted) along with the market moments to predict subsequent aggregate excess returns using the linear as well as the quantile regression model.FindingsThe authors report that both equal-weighted skewness and kurtosis significantly predict subsequent market returns in two countries, while value-weighted average skewness and kurtosis are significant in predicting returns in four out of nine sample markets. The results for quantile regression show that the relationship between the risk variable and aggregate returns varies along the spectrum of conditional quantiles.Originality/valueThis is the first study that investigates the impact of third and fourth higher-order average realized moments on the predictability of subsequent aggregate excess returns in the MSCI Asian emerging stock markets. This study is also the first to analyze the sensitivity of future market returns over various quantiles.

Highlights

The capital asset pricing model (CAPM) by Sharpe (1964) and Lintner (1965) is a widely recognized theory in the asset pricing literature
We examine the impact of kurtosis along with skewness, which has not been covered in the previous studies
We found that the average skewness and kurtosis significantly predict the subsequent market returns in a few countries only

Summary

Introduction

The capital asset pricing model (CAPM) by Sharpe (1964) and Lintner (1965) is a widely recognized theory in the asset pricing literature. The model asserts the existence of a linear relationship between the market beta (representing systematic risk) and excess returns. Studies in the highly diversified markets of the US, Europe and other developed economies found negative premiums on the market beta despite positive returns on the market portfolio, engendering an argument that the stock return premiums cannot be fully explained by adjusting only the systematic risk (Jensen-Gaard, 2014). Several studies (Ang et al, 2006, 2009; Baker et al, 2011; Frazzini and Pedersen, 2014; Beveratos et al, 2017; Blau, 2017) have found an inverted relationship between the excess returns of the stock and JEL Classification — G10, G12, G15, G17 © Sumaira Chamadia, Mobeen Ur Rehman and Muhammad Kashif. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Objectives

Results

Conclusion