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Non-Parametric Analysis of Hedge Fund Returns: New

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D S E
Working Paper
Crisis and Hedge Fund Risk
Monica Billio
Mila Getmansky
Loriana Pelizzon
Dipartimento Scienze Economiche
Department
of Economics
Ca’ Foscari University of
Venice
ISSN: 1827/336X
No. 10/WP/2008
Working Pap er s
Depar tmen t o f Economi c s
C a ’ F o s c a r i Un i v e r s i ty o f V e n i c e
No. 1 1 /WP/2008
ISSN 1827-336X
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Non-Parametric Analysis of Hedge Fund Returns: New
Insights from High Frequency Data
Monica Billio
University of Venice and SSAV, Scuola Studi Avanzati in Venezia
Mila Getmansky
Isenberg School of Management, University of Massachusetts
Loriana Pelizzon
University of Venice and SSAV, Scuola Studi Avanzati in Venezia
Abstract
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.
Keywords
Hedge Fund, Risk Management, High frequency data
JEL Codes
G12, G29, C51
Address for correspondence:
Loriana Pelizzon
Department of...

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Non-Parametric Analysis of Hedge Fund Returns: New. Anti Essays. Retrieved August 19, 2018, from the World Wide Web: https://www.antiessays.com/free-essays/Non-Parametric-Analysis-Hedge-Fund-Returns-New-11645.html