This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Fund-of-funds construction by statistical multiple testing methods

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Michael Wolf
Dan Wunderli
Abstract

Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical techniques. In particular, at a given point in time, we determine which funds significantly outperform a given benchmark while, crucially, accouting for the fact that a large number of funds are examined at the same time. This is achieved by employing so-called multiple testing methods. Then, the equal-weighted or the global minimum variance portfolio of the outperforming funds is held for one year, after which the selection process is repeated. When backtesting this strategy on two particular hedge fund universes, we find that the resulting FoF portfolios have attractive return properties compared to the 1/N portfolio (that is, simply equal-weighting all the available funds) but also when compared to two investable hedge fund indices.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.iew.unizh.ch/wp/iewwp445.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Institute for Empirical Research in Economics - IEW in its series IEW - Working Papers with number iewwp445.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Sep 2009
Date of revision:
Handle: RePEc:zur:iewwpx:445

Contact details of provider:

For technical questions regarding this item, or to correct its listing, contact: (Hanna Britt).

Related research
Keywords: Bootstrap; familywise error rate; fund-of-funds; performance evaluation;

Other versions of this item:

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Jobson, J D & Korkie, Bob M, 1981. "Performance Hypothesis Testing with the Sharpe and Treynor Measures," Journal of Finance, American Finance Association, vol. 36(4), pages 889-908, September. [Downloadable!] (restricted)
  2. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-58, May. [Downloadable!] (restricted)
    Other versions:
  3. Romano, Joseph P. & Shaikh, Azeem M. & Wolf, Michael, 2008. "Formalized Data Snooping Based On Generalized Error Rates," Econometric Theory, Cambridge University Press, vol. 24(02), pages 404-447, April. [Downloadable!]
    Other versions:
  4. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers iewwp320, Institute for Empirical Research in Economics - IEW. [Downloadable!]
  5. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July. [Downloadable!] (restricted)
    Other versions:
  6. Joseph P. Romano & Michael Wolf, 2005. "Stepwise Multiple Testing as Formalized Data Snooping," Econometrica, Econometric Society, vol. 73(4), pages 1237-1282, 07. [Downloadable!] (restricted)
  7. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December. [Downloadable!] (restricted)
  8. Kosowski, Robert & Naik, Narayan Y. & Teo, Melvyn, 2007. "Do hedge funds deliver alpha? A Bayesian and bootstrap analysis," Journal of Financial Economics, Elsevier, vol. 84(1), pages 229-264, April. [Downloadable!] (restricted)
  9. Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December. [Downloadable!] (restricted)
Full references

Statistics
Access and download statistics

Did you know? You can import bibliographic info in various formats into you bibliographic tool, or just into your word processor. See under "publisher info" on each abstract page.

This page was last updated on 2009-11-26.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.