The Predictability of Stock Market Returns in South Africa: Parametric vs. Non‐parametric Methods

Abstract

This paper compares the forecasting performance of a sub‐class of univariate parametric and non‐parametric models in predicting stock market returns in South Africa. To account for conditional heteroskedasticity in stock returns data, the non‐parametric model is generated by the conditional heteroskedastic non‐linear autoregressive (NAR) model, while the parametric model is produced by the generalised autoregressive conditional heteroskedastic in mean (GARCH‐M) model. The results of the paper show that the NAR as a non‐parametric model performs better than the GARCH‐M model in short‐term forecasting horizon, and this indicates the importance of a distribution‐free model in predicting stock returns in South Africa.

Weak Form Market Efficiency of the Johannesburg Stock Exchange: Pre, During and Post the 2008 Global Financial Crisis

“…In South Africa there are also a number of studies which have been carried out examining the efficiency of the stock market (Affleck-Graves, 1975;Smith and Jefferies, 2002;Magnusson and Wydick, 2002;Appiah-Kusi & Menyah, 2003;Mabhunu, 2004;Cubbin et al, 2006;Jefferies & Smith, 2008;Smith, 2008;Bonga-Bonga and Mwamba, 2011;Bonga-Bonga, 2012;Van Heerden et al, 2013). The studies also established mixed results.…”