2009 July 06

Jours fixes take place on the first monday of the month, starting at 5:00 p.m., in the House of Finance (Campus Westend).

[Timo Litty, E-Finance Lab]

For years, research has been conducted to correctly model and predict the risk and return structures of Private Equity funds. Although past research has revealed valuable insight into the features of those funds, most risk and return model struggle with the dispersion of PE funds` returns, their illiquidity and the factors driving the returns. The goal of this paper is to develop a methodology to correctly determine the risk and return profiles of Private Equity funds given their respective characteristics of management skill, investment focus and market dependency. We overcome the shortcomings of prior models by applying new methods like neural networks and Copulae which have not been used in this research field before in order to estimate market and management dependencies of returns as well as the correlations of Private Equity investments' default and outperformances. Our model offers investors the possibility to estimate the risk and return profile of any selected fund by the respective funds's management features, investment focus and market exposition. Investors will thereby be able to choose a fund which matches their desired risk and return expectations, enabling investors to maximize their investment utility.