Linear Factor Models in Finance
Combining actual quantitative finance experience with analytical research, this book covers the science of asset pricing by concentrating on the most widely used modelling technique called linear factor modelling.
TABLE OF CONTENTS Linear Factor Models in Finance
Chapter 9: Predictability of Fund of Hedge Fund Returns Using DynaPorte
Greg N. Gregoriou [*] and Fabrice Rouah [ ]
Abstract
We utilize a linear factor model to regress various funds of hedge fund indices on macroeconomic variables and market factors. Our goal is challenging since FOF returns are non-normal and have an indirect exposure to common factors used for predicting hedge fund returns. We identify a new set of factors that could predict FOF returns.
[*] Greg N. Gregoriou is assistant professor of finance and faculty research coordinator in the School of Business and Economics at the State University of New York (Plattsburgh). E-mail: greg.gregoriou@plattsburgh.edu. Tel: (518) 564-4202.
[ ] Fabrice Rouah is the Institut de Finance Math matique de Montr al Scholar and PhD candidate (Finance) at McGill University, Montreal, Quebec. E-mail: fabrice.rouah@mail.mcgill.ca. We would like to thank Richard E.Oberuc at Burlington Hall Asset Management for providing us with the DynaPorte TM software (www.dynaporte.com).
9.1 Introduction
Over the last two years of high volatility in US stock markets, pension funds, university endowments, and high net worth individuals have turned to funds of hedge funds (FOFs) for downside protection (Schneeweis et al. (2001); Lhabitant (2002)). The majority of these investors do not feel qualified to construct a portfolio of hedge funds on their own. FOFs are popular because they invest in other hedge funds and can spread the risk among many different hedge fund strategies. FOF managers monitor the managers in the basket, relieving their clients of the complicated process of selection, due diligence, and periodic monitoring of individual hedge funds.
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