Hedge Fund Networks

Abstract

Network theory helps to resolve allocation problems and issues of systematic risk propagation in hedge fund networks because it allows for the hedge funds to be shown as interacting entities. Importance scores and cluster analysis support the understanding of risk propagation and causality, and capture the time-varying interconnectedness among hedge fund strategies. Furthermore, considering cluster affiliation, network metrics derived from importance scores help separate active management from active risk monitoring and build diversified portfolios. Hedge fund indexes with large centrality scores are less meaningful as risk indicators because the importance scores are time-varying. Hedge fund indexes with low centrality scores are weakly connected, but their diversification and return enhancement advantages are time-varying. Correlation networks use asset prices, are the most widely used graphs, and are easy to implement. However, the difference between directed and correlation networks is one of the most important factors because there is a direction in risk flow.