Non-Parametric Analysis of Hedge Fund Returns: New Insights from High Frequency Data

Journal of Alternative Investments (forthcoming)

https://doi.org/10.3905/JAI.2009.12.1.021

Posted: 22 May 2019

See all articles by Monica Billio

Monica Billio

University of Venice - Department of Economics; Ca Foscari University of Venice - Dipartimento di Economia

Mila Getmansky Sherman

University of Massachusetts at Amherst - Eugene M. Isenberg School of Management - Department of Finance

Loriana Pelizzon

Goethe University Frankfurt - Faculty of Economics and Business Administration; Leibniz Institute for Financial Research SAFE; Ca Foscari University of Venice - Dipartimento di Economia

Date Written: April 12, 2009

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.

Keywords: Hedge Funds, Risk Management, High frequency data

JEL Classification: G12, G29, C51

Suggested Citation

Billio, Monica and Billio, Monica and Getmansky Sherman, Mila and Pelizzon, Loriana, Non-Parametric Analysis of Hedge Fund Returns: New Insights from High Frequency Data (April 12, 2009). Journal of Alternative Investments (forthcoming), https://doi.org/10.3905/JAI.2009.12.1.021 , Available at SSRN: https://ssrn.com/abstract=1130715 or http://dx.doi.org/10.2139/ssrn.1130715

Monica Billio (Contact Author)

University of Venice - Department of Economics ( email )

Fondamenta San Giobbe 873
Venezia 30121
Italy
+39 041 234 9170 (Phone)
+39 041 234 9176 (Fax)

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

HOME PAGE: http://www.unive.it/persone/billio

Mila Getmansky Sherman

University of Massachusetts at Amherst - Eugene M. Isenberg School of Management - Department of Finance ( email )

Amherst, MA 01003-4910
United States

Loriana Pelizzon

Goethe University Frankfurt - Faculty of Economics and Business Administration ( email )

Theodor-W.-Adorno-Platz 3
Frankfurt am Main, D-60323
Germany

Leibniz Institute for Financial Research SAFE ( email )

Theodor-W.-Adorno-Platz 3
Frankfurt am Main, 60323
Germany

HOME PAGE: http://www.safe-frankfurt.de

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

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