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Social networks and idiosyncratic risk in the hedge funds industry

Final Report Summary - SNIR (Social networks and idiosyncratic risk in the hedge funds industry)

This project probes the social networks that exist in one of the world's most important but least well-documented industries: The hedge fund sector of the investment management industry. There are about 10 000 hedge funds world wide of significance, and the industry is global in scale and as of the end of 2008 controlled around USD 1 800 billion in assets.

Yet, because of its private nature, it is not well documented and appears secretive. From an academic perspective, as explained in the original SNIR proposal, studying this industry gives an opportunity to examine the relationship between social networks, risk taking and performance in an unusually interesting setting. From a policy perspective, answering questions about the behaviour of hedge funds will assist EU and national government legislators who are concerned to regulate further the activities of alternative investment funds.

The project has carefully reviewed the literature and interacted with scholars in specially organised seminars and at international conferences, and so has developed a better understanding of how to theorise the relationships between networks, risk taking and performance. As is well known, markets can be conceptualised not only as systems of exchange, but also as networks of relationships (White, 1981; Granovetter, 1985).

And it is now clearer that the literature is ambiguous about some relationships and unclear about others:

- There is a potentially ambiguous link between networks and performance. Direct ties potentially yield benefits such as knowledge sharing, complementarities, and scale (Arora and Gambardella, 1990; Powell, Koput, and Smith-Doerr, 1996; Ahuja, 2000). Indirect ties can also represent a channel for communicating, transferring information, and facilitating knowledge exchange (Gulati and Gargiulo, 1999). As clearly explained (Podolny, 1994; Gulati, 1995; Gulati, 1998), actors benefit from a favourable network position as well as from the resources they can access from their alters. Yet, against this view, there is a dark side of networks. Myopia, information overload, and cognitive overloading can mean that actors that are more central do not perform so well.

- Network linkages may also influence risk taking behaviour, again in potentially two ways. On the one side, being central gives an actor power, and the ability to take more risks, and avoid the down side due to agency mismatching. On the other hand, many argue that powerful actors are less prone to take risk because they may lose access to and control over valued resources (Anderson and Galinsky 2006). This logic of the powerful having more to lose by taking risks would also appear to be consistent with prospect theory (Kahneman and Tversky, 1979).

Collecting data on the hedge fund industry has been very challenging, as this is a secretive industry. It formed a significant part of the overall project work:

- We identified authoritative data on more than 2 000 hedge funds worldwide, obtaining information about their investment performance as well as information on their network linkages with 120 prime brokers, which include the major investment banks such as Goldman Sachs as well as many smaller institutions. These links form a key element in our analysis. (Prime Brokers are investment institutions that work with hedge funds to provide a vast array of services such as trading services, security and financial lending and operational support. Picking the right prime brokerage firm is one of the most important steps to starting a successful hedge fund.)

- We have undertaken selective interviews with important industry actors to deepen our understanding of the industry, including prime brokers, hedge fund managers, investment analysts and regulatory bodies.

Because data collection and data coding has been so challenging, our analysis is not yet complete. However, our initial results are very exciting.