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Non-Parametric Analysis of Hedge Fund Returns: New Insights from High Frequency DataMonica BillioCa Foscari University of Venice - Department of Economics Mila GetmanskyUniversity of Massachusetts at Amherst - Eugene M. Isenberg School of Management - Department of Finance & Operations Management Loriana PelizzonCa Foscari University of Venice - Department of Economics April 12, 2009 Journal of Alternative Investments (forthcoming) Abstract: This paper examines four daily hedge fund return indices: MSCI, FTSE, Dow Jones, and HFRX, all based on investable hedge funds, and three monthly hedge fund return indices: CSFB Tremont, CISDM, and HFR, which comprise both investable and non-investable hedge funds. Our study, based on standard statistical analysis, non-parametric analysis of the return distribution, and non-parametric regressions with respect to the S&P 500 index shows that key biases like fund selection, asset liquidity, data frequency, sample period, and index construction methodologies are responsible for different statistical properties of hedge fund indices. One key variable that highly affects the statistical properties of hedge fund index returns is the “investability” of hedge fund indices.
Number of Pages in PDF File: 39 Keywords: Hedge Funds, Risk Management, High frequency data JEL Classification: G12, G29, C51 working papers seriesDate posted: May 20, 2008 ; Last revised: April 25, 2012Suggested CitationContact Information
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