Portfolio optimisation using alternative risk measures

Abstract

Markowitz’ Modern Portfolio Theory (MPT) optimises the ratio of mean portfolio returns and portfolio risk in the form of the variance of returns, giving rise to criticism relating to, inter alia, minimising upside risk, the assumption of normally-distributed returns, and a failure to recognise heteroskedasticity. In addressing these criticisms, this research investigates the use of alternative risk measures to optimise risk and return in MPT investment strategies using non-parametric numerical methods to optimise portfolios comprising assets from the S&P 1200 and MSCI GICS world indices. It investigates, in particular, downside semivariance, downside semideviation, mean absolute deviation, semi-absolute deviation, value at risk and conditional value at risk. In addition, the study investigates optimisation using backward-looking and forward-looking risk measures through exponentially-weighted moving average forecasts of risk measures and return. In general, all the alternative risk measures investigated result in investment strategies with higher returns than traditional MPT variance-optimised strategies, with semi-absolute deviation-optimised strategies performing best of all. The introduction of risk and return forecasting does not materially impact on strategy performance.