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Out-of-sample Predictability of the South African Equity Risk Premium Distribution: A Quantile Regression Approach

Author

Listed:
  • Munyaradzi Chawana
  • Ilse Botha
  • Yolanda Stander

    (S&P Global Ratings)

Abstract

This paper explores the out-of-sample predictability of the South African equity risk premium (ERP) distribution through a quantile regression framework. Empirical results show that beyond central quantiles, several predictor variables exhibit statistically and economically significant predictive ability, reinforcing evidence against the location shift hypothesis which proposes that predictor variables affect only the location of the ERP conditional distribution. Furthermore, combining out-ofsample forecasts from various parts of the ERP distribution, a robust out-of-sample approximation of the mean ERP is attained under a 5-quantile post- least absolute shrinkage and selection operator specification with a time-invariant weighting scheme.

Suggested Citation

  • Munyaradzi Chawana & Ilse Botha & Yolanda Stander, 2022. "Out-of-sample Predictability of the South African Equity Risk Premium Distribution: A Quantile Regression Approach," The African Finance Journal, Africagrowth Institute, vol. 24(2), pages 51-65.
    • Handle: RePEc:afj:journl:v:24:y:2022:i:2:p:51-65
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    File URL: https://journals.co.za/doi/abs/10.10520/ejc-finj_v24_n2_a4
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    More about this item

    Keywords

    Quantile regression; Equity risk premium; Out-of-sample predictability; Forecast combination;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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