Non-Parametric Analysis of Hedge Fund Returns: New Insights from High Frequency Data
This paper examines four different daily datasets of hedge fund return indexes: MSCI, FTSE, Dow Jones and HFRX, all based on investable hedge funds, and three different monthly datasets of hedge fund return indexes: CSFB, CISDM and HFR which comprise both investable and non-investable hedge funds. Our study, based on standard statistical analysis, non-parametric analysis of the distribution and non-parametric regressions with respect to the S&P500 index shows that key data biases and disparate index construction methodologies lead to different statistical properties of hedge fund databases. One key variable that highly affects the statistical properties of hedge fund index returns is the �investability� of hedge funds
|Date of creation:||2008|
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- Vikas Agarwal, 2004. "Risks and Portfolio Decisions Involving Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 63-98.
- Billio, Monica & Getmansky, Mila & Pelizzon, Loriana, 2012.
"Dynamic risk exposures in hedge funds,"
Computational Statistics & Data Analysis,
Elsevier, vol. 56(11), pages 3517-3532.
- Monica Billio & Mila Getmansky & Loriana Pelizzon, 2007. "Dynamic Risk Exposure in Hedge Funds," Working Papers 2007_17, Department of Economics, University of Venice "Ca' Foscari".
- Fung, William & Hsieh, David A, 1997. "Empirical Characteristics of Dynamic Trading Strategies: The Case of Hedge Funds," Review of Financial Studies, Society for Financial Studies, vol. 10(2), pages 275-302. Full references (including those not matched with items on IDEAS)
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