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Structural Breaks and GARCH Models of Stock Return Volatility: The Case of South Africa

Author

Listed:
  • Ali Babikir

    (Department of Economics, University of Pretoria and South African Treasury, Pretoria, South Africa)

  • Rangan Gupta

    (Department of Economics, University of Pretoria)

  • Chance Mwabutwa

    (Department of Economics, University of Pretoria and South African Treasury, Pretoria, South Africa)

  • Emmanuel Owusu-Sekyere

    (Department of Economics, University of Pretoria and South African Treasury, Pretoria, South Africa)

Abstract
This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests and daily returns for the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural breaks in the unconditional variance of the stock returns series over the period, with high levels of persistence and variability in the parameter estimates of the GARCH (1, 1) model across the sub-samples defined by the structural breaks. This indicates that structural breaks are empirically relevant to stock return volatility in South Africa. In out-of-sample tests, we find that combining forecasts from different benchmark and competing models that accommodate structural breaks in volatility improves the accuracy of volatility forecasting. Furthermore, for shorter horizons, the MS-GARCH model better captures asymmetry in stock return volatility than the GJR-GARCH (1, 1) model, which better suited to longer horizons, but in general, the asymmetric models fail to outperform the GARCH (1,1) model.

Suggested Citation

  • Ali Babikir & Rangan Gupta & Chance Mwabutwa & Emmanuel Owusu-Sekyere, 2010. "Structural Breaks and GARCH Models of Stock Return Volatility: The Case of South Africa," Working Papers 201030, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201030
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    stock return volatility; structural breaks; in-sample tests; out-of-sample tests; GARCH Models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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