Abstract

This article re-examines the return predictability of eight African stock markets. When returns of stocks are predictable, arbitrageurs make abnormal gains from analyzing prices. The study uses a non-parametric Generalised Spectral (GS) test in a rolling window approach. The rolling window approach tracts the periods of efficiency over time. The GS test is robust to conditional heteroscedasticity and it detects the presence of linear and nonlinear dependencies in a stationary time series. Our results support the Adaptive Market Hypothesis (AMH). This is because, indices whose returns were observed to be predictable by analyzing them in absolute form and therefore weak - form inefficient showed trends of unpredictability in a rolling window.

Highlights

  • Introduction and Literature ReviewThe Efficient Market Hypothesis (EMH) postulated by Fama (1970) states that available information on a particular market is reflected in setting current security prices

  • We apply the Generalised spectral test to compute the p-values on the full sample

  • Egypt, one of the oldest markets in Africa was found to be highly predictable and weak-form inefficient when the analysis was done in absolute form

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Summary

Introduction

Introduction and Literature ReviewThe Efficient Market Hypothesis (EMH) postulated by Fama (1970) states that available information on a particular market is reflected in setting current security prices. Studies on the weak-form type of the EMH on African stock markets that have been reported in the literature are that of Jammine & Hawkins (1974), Affleck-Graves & Money (1975), Dickinson & Muragu(1994), Osei(1998), Olowe(1999), Bundoo(2000), Magnusson & Wydick (2002), Smith et al (2002), Appiah-Kusi & Menyah (2003), Simons & Laryea (2005), Jefferis & Smith (2005), Smith (2008), Mollah & Vitali (2011), Ntim et al (2011b) and Gyamfi et al (2016a, 2016b) These studies have ended with mixed conclusions. This work employs the relative efficiency reasoning which is consistent with the Adaptive Markets Hypothesis (AMH) of Lo (2004, 2005)

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