Midori Munechika

(Toyo University, Japan)

 

 

Abstract: This paper applies ARMA-GARCH-type modeling to shed light on the persistence of performance and volatility of daily management hedge fund index returns from April 1, 2003 to August 11, 2014. Time series data of four principal hedge fund strategy indices (Equity Hedge, Event Driven, Macro/CTA, Relative Value Arbitrage) have peculiar characteristics — that is, serially correlated and volatility clustered returns. In addition, their unconditional distributions are heavy-tailed and negatively skewed. Hedge funds are generally free to change their trading strategies as market conditions evolve. This flexibility is a distinctive feature that delivers hedge fund returns. At the same time, it is possible to say that this feature potentially amplifies market volatility. Therefore, a rolling application of ARMA-GARCH modeling can potentially capture the broad shift of performance and volatility persistence in the investment strategy, especially in the period surrounding the financial crisis of 2007-2009. The empirical results show important differences concerning persistence performance between the directional and the mispricing strategies. Moreover, the Macro/CTA strategy only indicates a negative news impact. Finally, time-varying parameter estimations reveal that Macro/CTA was strongly affected by the isolated outliers during the financial crisis.

 

 

Key words: hedge funds; rolling ARMA-GARCH modeling; serial correlation; asymmetric volatility; index investing

 

JEL codes: C2, G1, G2