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 | |
State | Published - Feb 2006 |
Funding
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.
Keywords
- Expected regret
- Fund of funds
- Hedge funds
- Monte Carlo simulation
- Portfolio choice
- Portfolio optimization
ASJC Scopus subject areas
- Finance
- Economics and Econometrics