Time-varying asset allocation across hedge fund indices

Abstract

This paper looks at the risk-adjusted performance of dynamic asset allocation strategies across hedge fund indices using conditional volatility forecasting methods for constructing optimal portfolios for funds of funds. Monthly out-of-sample comparisons for nine Credit Suisse First BostonTremont hedge fund indices, as well as weekly and daily rebalanced dynamic portfolios are examined for the three main sub-indices of Standard & Poor's (S&P) Hedge Fund Index. A multivariate asymmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model is also considered for portfolio construction using daily S&P Hedge Fund sub-indices data. Most hedge fund indices exhibit time-varying volatility and volatility clustering. Accounting for forecasted next-period volatility generates portfolios with the best risk-return profile among all portfolios under consideration. After accounting for transaction costs, out-of-sample results indicate that all dynamic hedge fund index portfolios largely outperform the S&P 500 Index, both on an expected return and risk-adjusted return basis. © 2009 Palgrave Macmillan.