Pricing and risk management of hedge funds : a new framework

We propose a new framework for the analysis of hedge funds and the modelling of their per- formance. This approach is based on our finding that the investment styles declared by fund managers are unreliable and are uninformative about fund performance. The framework has been designed to cluster hedge funds using an innovative technique based on artificial neural networks. The framework is tested on a large selection of different data sets and the resulting clusters provide the best matches with known solutions when compared to existing methods. The framework applied to hedge funds is a valuable fund management tool as funds are categorised in terms of their performance alone. The universe of hedge fund is best represented by 12 clusters, each corresponding to a different pattern of returns. The clusters are shown to be stable over time and this indicates that the framework will continue to be a reliable representation of the hedge fund market after the Global Credit Crisis. We demonstrate that the framework allows the construction of a more efficient frontier of portfolios by diversifying across the clusters identified rather than using investment styles. A multi-factor model is built using these clusters; it dominates all comparable models in the ability to explain fund returns. It allows managerial skill to be.estimated more accurately, leading to a better valuation of hedge funds and fund of hedge funds.EThOS - Electronic Theses Online ServiceGBUnited Kingdo