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Volatility Modelling of the Johannesburg Stock Exchange All Share Index Using the Family GARCH Model

Author

Listed:
  • Israel Maingo

    (Department of Mathematical and Computational Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, Limpopo, South Africa
    These authors contributed equally to this work.)

  • Thakhani Ravele

    (Department of Mathematical and Computational Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, Limpopo, South Africa
    These authors contributed equally to this work.)

  • Caston Sigauke

    (Department of Mathematical and Computational Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, Limpopo, South Africa
    These authors contributed equally to this work.)

Abstract

In numerous domains of finance and economics, modelling and predicting stock market volatility is essential. Predicting stock market volatility is widely used in the management of portfolios, analysis of risk, and determination of option prices. This study is about volatility modelling of the daily Johannesburg Stock Exchange All Share Index (JSE ALSI) stock price data between 1 January 2014 and 29 December 2023. The modelling process incorporated daily log returns derived from the JSE ALSI. The following volatility models were presented for the period: sGARCH(1, 1) and fGARCH(1, 1). The models for volatility were fitted using five unique error distribution assumptions, including Student’s t , its skewed version, the generalized error and skewed generalized error distributions, and the generalized hyperbolic distribution. Based on information criteria such as Akaike, Bayesian, and Hannan–Quinn, the ARMA(0, 0)-fGARCH(1, 1) model with a skewed generalized error distribution emerged as the best fit. The chosen model revealed that the JSE ALSI prices are highly persistent with the leverage effect. JSE ALSI price volatility was notably influenced during the COVID-19 pandemic. The forecast over the next 10 days shows a rise in volatility. A comparative study was then carried out with the JSE Top 40 and the S&P500 indices. Comparison of the FTSE/JSE Top 40, S&P 500, and JSE ALLSI return indices over the COVID-19 pandemic indicated higher initial volatility in the FTSE/JSE Top 40 and S&P 500, with the JSE ALLSI following a similar trend later. The S&P 500 showed long-term reliability and high rolling returns in spite of short-run volatility, the FTSE/JSE Top 40 showed more pre-pandemic risk and volatility but reduced levels of rolling volatility after the pandemic, similar in magnitude for each index with low correlations among them. These results provide important insights for risk managers and investors navigating the South African equity market.

Suggested Citation

  • Israel Maingo & Thakhani Ravele & Caston Sigauke, 2025. "Volatility Modelling of the Johannesburg Stock Exchange All Share Index Using the Family GARCH Model," Forecasting, MDPI, vol. 7(2), pages 1-33, April.
    • Handle: RePEc:gam:jforec:v:7:y:2025:i:2:p:16-:d:1627857
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