Abstract

The authors discuss a network-based methodology that models hedge fund strategies across the superordinate–subordinate dimension to gain new insights into their interrelation. This methodology uncovers considerable misbehavior of various hedge fund strategies from the network perspective. Simply speaking, a misbehaving hedge fund strategy has undesired network proximity (similarity) with strategies from other classifications and/or undesired network-based risk properties. The authors conduct extensive static and dynamic (bootstrapping) analyses demonstrating misbehaviors for the full-sample data set. In addition, they demonstrate that numerous network-based behavioral properties of hedge fund strategies can explain future hedge fund returns. This aspect is of significant relevance, as it shows that network-based information has the potential to act as a value-adding warning indicator for funds of hedge funds. Summing up, the authors think that this article provides novel and valuable tools for hedge fund investors, managers, and analysts. TOPICS:Real assets/alternative investments/private equity, performance measurement

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