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Asymmetric risk and return: Evidence from the Australian Stock Exchange

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  • Vo, Minh
  • Cohen, Michael
  • Boulter, Terry

Abstract

This paper examines volatility asymmetry in a financial market using a stochastic volatility framework. We use the MCMC method for model estimations. There is evidence of volatility asymmetry in the data. Our asymmetric stochastic volatility in mean model, which nests both asymmetric stochastic volatility (ASV) and stochastic volatility in mean models (SVM), indicates ASV sufficiently captures the risk-return relationship; therefore, augmenting it with volatility in mean does not improve its performance. ASV fits the data better and yields more accurate out-of-sample forecasts than alternatives. We also demonstrate that asymmetry mainly emanates from the systematic parts of returns. As a result, it is more pronounced at the market level and the volatility feedback effect dominates the leverage effect.

Suggested Citation

  • Vo, Minh & Cohen, Michael & Boulter, Terry, 2015. "Asymmetric risk and return: Evidence from the Australian Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 558-573.
    • Handle: RePEc:eee:pacfin:v:35:y:2015:i:pb:p:558-573
    DOI: 10.1016/j.pacfin.2015.10.003
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    Cited by:

    1. Minh Vo, 2025. "Measuring and Forecasting Stock Market Volatilities with High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3503-3544, June.

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    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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