Hedge Fund Investment Through Piecewise Linear Regression and Optimization
Purdue University - Krannert School of Management
September 8, 2007
It is conjectured that the size of a hedge fund has some impact on its return. In this paper, we investigate the relationship between them and apply the results to construct an investment model. We first implement a learning algorithm to construct a piecewise linear regression model which shows that a fund's AUM (Asset Under Management) has different effects in different situations on its return. Then, with consideration of the various scenarios, we propose a robust optimization model to maximize the expected profit. Finally, we present the computational results that illustrate the strength of our two-stage procedure.
Number of Pages in PDF File: 15
Keywords: hedge fund, piecewise linear regression, portfolio optimization
JEL Classification: C44, C45
Date posted: March 27, 2007
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