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Random matrix theory and fund of funds portfolio optimisation

Conlon, Thomas and Ruskin, Heather J. and Crane, Martin (2007) Random matrix theory and fund of funds portfolio optimisation. Physica A: Statistical Mechanics and its Applications, 382 (2). pp. 565-576. ISSN 0378-4371

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The proprietary nature of Hedge Fund investing means that it is common practise for managers to release minimal information about their returns. The construction of a Fund of Hedge Funds portfolio requires a correlation matrix which often has to be estimated using a relatively small sample of monthly returns data which induces noise. In this paper random matrix theory (RMT) is applied to a cross-correlation matrix C, constructed using hedge fund returns data. The analysis reveals a number of eigenvalues that deviate from the spectrum suggested by RMT. The components of the deviating eigenvectors are found to correspond to distinct groups of strategies that are applied by hedge fund managers. The Inverse Participation ratio is used to quantify the number of components that participate in each eigenvector. Finally, the correlation matrix is cleaned by separating the noisy part from the non-noisy part of C. This technique is found to greatly reduce the difference between the predicted and realised risk of a portfolio, leading to an improved risk profile for a fund of hedge funds.

Item Type:Article (Published)
Uncontrolled Keywords:random matrix theory; hedge funds; fund of funds; correlation matrix; portfolio optimisation;
Subjects:Business > Finance
Mathematics > Statistics
Mathematics > Probabilities
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:
Copyright Information:Copyright © 2007 Elsevier
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:14833
Deposited On:08 Sep 2009 16:48 by Martin Crane. Last Modified 08 Sep 2009 16:48

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