This paper features a tri-criteria analysis of Eurekahedge fund data strategy index data. We use nine Eurekahedge equally weighted main strategy indices for the portfolio analysis. The tri-criteria analysis features three objectives: return, risk and dispersion of risk objectives in a Multi-Criteria Optimisation (MCO) portfolio analysis. We vary the MCO return and risk targets and contrast the results with four more standard portfolio optimisation criteria, namely the tangency portfolio (MSR), the most diversifed portfolio (MDP), the global minimum variance portfolio (GMW), and portfolios based on minimising expected shortfall (ERC). Backtests of the chosen portfolios for this hedge fund data set indicate that the use of MCO is accompanied by uncertainty about the a priori choice of optimal parameter settings for the decision criteria. The empirical results do not appear to outperform more standard bi-criteria portfolio analyses in the backtests undertaken on our hedge fund index data.

Additional Metadata
Keywords Keywords: MCO, Portfolio Analysis, Hedge Fund Strategies, Multi-Criteria Optimisation, Genetic Algorithms.
JEL International Financial Markets (jel G15), Financial Forecasting (jel G17), Financing Policy; Capital and Ownership Structure (jel G32), Financial Econometrics (jel C58), Financial Markets (jel D53)
Persistent URL hdl.handle.net/1765/98658
Series Econometric Institute Research Papers
Citation
Allen, D.E, McAleer, M.J, & Singh, A.K. (2016). A Multi-Criteria Portfolio Analysis of Hedge Fund Strategies. Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/98658