A Network Approach to Analyzing Hedge Fund Connectivity

Abstract

In this article, the authors investigate the hedge fund market as a network of interacting individual funds. The authors identify and analyze the most important hedge fund styles that could both affect the market and transmit systemwide shocks to other funds, individual asset classes, and beyond. The authors find that the most connected hedge fund database categories are global macro and equity long–short funds. A central result of the article is a classification of funds using clustering, in which seemingly different funds are shown to cluster based on their shared factor exposures. This finding demonstrates that investors should consider fund connectivity and their attendant importance scores rather than database classifications when measuring hedge fund risk across the business cycle. The authors also provide a forecasting framework that can be used to predict hedge fund network behavior and the impact of individual factors on the network.

TOPICS: Analysis of individual factors/risk premia, factor-based models, style investing, performance measurement

Key Findings

• • The hedge fund universe can be represented as a graph that depicts the relational structure and interaction among individual hedge funds.

• • Clustering algorithms are used to classify and evaluate hedge fund styles as well as individual hedge funds. Hedge fund networks are found to have different dynamics across different stages of the business cycle.

• • Various hedge funds are found to be connected based on factor exposure in ways that stand in contrast to their database categorizations; applying LASSO helps to identify factor exposure in the clusters and to predict network behavior.