Portfolio optimisation using alternative risk measures
Douglas Austen Lorimer,
Cornelis Hendrik van Schalkwyk and
Jan Jakub Szczygielski
Finance Research Letters, 2024, vol. 67, issue PA
Abstract:
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.
Keywords: Portfolio optimisation; Returns; Sharpe ratio; Risk measures; Forecasting; Exponentially weighted moving average (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1544612324007888
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:67:y:2024:i:pa:s1544612324007888
DOI: 10.1016/j.frl.2024.105758
Access Statistics for this article
Finance Research Letters is currently edited by R. Gençay
More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().