Performance measurement for hedge funds with neural network derived benchmarks
| Dec 18th, 2006 | Filed under: Academic Research, Performance, Analytics & Metrics | By: Alpha Male |
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By: Ramin Baghai-Wadji & Stefan Klocker, Vienna University of Economics and Business Administration
Published: May 20, 2006
Assuming hedge fund beta exists, determining the amount of alpha produced by a manager requires one to know what particular hedge fund beta a manager is leveraging. So the identification of a hedge fund as being say, ”merger arb” or “distressed” is critical in determining value added by the manager.
Problem is, asking managers to self identify may not always be the best strategy. Managers would face a fundamental conflict as their choice might make them look like a hero or a dog.
This paper was first presented in October 2006 at the Annual Meeting of the German Finance Association. It proposes a new methodology for identifying the strategies of hedge funds by grouping them together into natural clusters using a “self-organizing map” (a.k.a. “a neural network”).
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