Portfolio optimisation using alternative risk measures

• Published in: Finance research letters Vol. 67; p. 105758
• Main Authors: Lorimer, Douglas Austen, van Schalkwyk, Cornelis Hendrik, Szczygielski, Jan Jakub
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.09.2024
• Subjects: Exponentially weighted moving average; Forecasting; Portfolio optimisation; Returns; Risk measures; Sharpe ratio; Sharpe ratio; Returns; Exponentially weighted moving average; Forecasting; Risk measures; Portfolio optimisation
• ISSN: 1544-6123; 1544-6131
• DOI: 10.1016/j.frl.2024.105758

•We optimise investment portfolios using alternative raw and forecasted risk measures.•The use of asymmetric risk measures results in superior portfolio returns.•Risk measures incorporating unsquared deviations outperform those incorporating squared deviations.•Results are consistent across the pre-COVID-19 and COVID-19 periods.•Optimising portfolios using EWMA risk measure forecasts does not result in statistically significant improvements in portfolio returns. We use a numerical methods algorithm based on gradient descent to optimise investment portfolios of global indices using raw and forecasted risk measures at differing frequencies. The results permit a comparison of how the characteristics of risk measures other than the variance and standard deviation impact portfolio performance. Asymmetric risk measures result in superior portfolio returns, while risk measures incorporating unsquared deviations outperform those incorporating squared deviations. Risk measures forecasted using the exponentially weighted moving average (EWMA) methodology do not yield significant increases in portfolio returns. Semi-absolute deviation, mean absolute deviation and downside semi-deviation perform favourably in producing higher returns.