Efficient fund of hedge funds construction under downside risk measures

David P. Morton; Elmira Popova; Ivilina Popova

doi:10.1016/j.jbankfin.2005.04.016

Efficient fund of hedge funds construction under downside risk measures

David P. Morton, Elmira Popova, Ivilina Popova^*

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices.

Original language	English (US)
Pages (from-to)	503-518
Number of pages	16
Journal	Journal of Banking and Finance
Volume	30
Issue number	2
DOIs	https://doi.org/10.1016/j.jbankfin.2005.04.016
State	Published - Feb 2006

Keywords

Expected regret
Fund of funds
Hedge funds
Monte Carlo simulation
Portfolio choice
Portfolio optimization

ASJC Scopus subject areas

Finance
Economics and Econometrics

Access to Document

10.1016/j.jbankfin.2005.04.016

Cite this

@article{e3d4fdf368ae44438961b4fdc192e6a2,

title = "Efficient fund of hedge funds construction under downside risk measures",

abstract = "We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices.",

keywords = "Expected regret, Fund of funds, Hedge funds, Monte Carlo simulation, Portfolio choice, Portfolio optimization",

author = "Morton, {David P.} and Elmira Popova and Ivilina Popova",

note = "Funding Information: This research was sponsored by Deutsche Asset Management, Deutsche Bank, New York. Much of the work was done while Ivilina Popova was a Director, and David Morton and Elmira Popova were consultants, at the Global Research Center of Deutsche Asset Management, New York. David Morton{\textquoteright}s work was also partially supported by the National Science Foundation under Grants DMI-9702217 and DMI-0217927. ",

year = "2006",

month = feb,

doi = "10.1016/j.jbankfin.2005.04.016",

language = "English (US)",

volume = "30",

pages = "503--518",

journal = "Journal of Banking and Finance",

issn = "0378-4266",

publisher = "Elsevier",

number = "2",

}

TY - JOUR

T1 - Efficient fund of hedge funds construction under downside risk measures

AU - Morton, David P.

AU - Popova, Elmira

AU - Popova, Ivilina

N1 - Funding Information: This research was sponsored by Deutsche Asset Management, Deutsche Bank, New York. Much of the work was done while Ivilina Popova was a Director, and David Morton and Elmira Popova were consultants, at the Global Research Center of Deutsche Asset Management, New York. David Morton’s work was also partially supported by the National Science Foundation under Grants DMI-9702217 and DMI-0217927.

PY - 2006/2

Y1 - 2006/2

N2 - We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices.

AB - We consider portfolio allocation in which the underlying investment instruments are hedge funds. We consider a family of utility functions involving the probability of outperforming a benchmark and expected regret relative to another benchmark. Non-normal return vectors with prescribed marginal distributions and correlation structure are modeled and simulated using the normal-to-anything method. A Monte Carlo procedure is used to obtain, and establish the quality of, a solution to the associated portfolio optimization model. Computational results are presented on a problem in which we construct a fund of 13 CSFB/Tremont hedge-fund indices.

KW - Expected regret

KW - Fund of funds

KW - Hedge funds

KW - Monte Carlo simulation

KW - Portfolio choice

KW - Portfolio optimization

UR - http://www.scopus.com/inward/record.url?scp=32944456930&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=32944456930&partnerID=8YFLogxK

U2 - 10.1016/j.jbankfin.2005.04.016

DO - 10.1016/j.jbankfin.2005.04.016

M3 - Article

AN - SCOPUS:32944456930

SN - 0378-4266

VL - 30

SP - 503

EP - 518

JO - Journal of Banking and Finance

JF - Journal of Banking and Finance

IS - 2

ER -

Efficient fund of hedge funds construction under downside risk measures

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this