A Heuristic Approach to Hedge Fund Allocation
Unlike traditional investment vehicles, hedge funds seem to produce return distributions with significantly non-normal skewness and kurtosis. This article introduces a practical heuristic approach using the semi-variance (that better accounts for non-normality in hedge fund returns) as a measure for downside risk. This heuristic approach provides better forecasts, stable portfolio allocations, and more diversification than the optimization approach. This article focuses on the relatively new but high-potential Asian hedge fund industry. The key to a successful portfolio allocation decision is to have very good estimates for risk and return. The make-up of the portfolio can be determined heuristically through risk-return ratios at the general asset class level, at the mutual fund level, and at the individual stock level, and running an optimizer to determine asset allocation by itself does not add value to a portfolio. It is the selection of assets and the careful determination of risk and return measure that the managers input to the optimization or the heuristic algorithm decision that provides the value-add.
Journal of Wealth Management
PHOON, Kok Fai; Fang, V.; and Yi, V..
A Heuristic Approach to Hedge Fund Allocation. (2008). Journal of Wealth Management. 10, (4), 42-52. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/1515
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