Asymmetric risk and return: Evidence from the Australian Stock Exchange

• We examine the volatility asymmetry using stochastic volatility framework.
• We develop the asymmetric stochastic volatility in mean model.
• Asymmetric stochastic volatility model outperforms alternatives in terms of goodness-of-fit and out-of-sample forecast.
• Asymmetry mainly emanates from the systematic parts of returns.
• Volatility feedback effect dominates leverage effect.

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.