| Issue |
RAIRO-Oper. Res.
Volume 49, Number 4, October-December 2015
|
|
|---|---|---|
| Page(s) | 821 - 844 | |
| DOI | https://doi.org/10.1051/ro/2015007 | |
| Published online | 08 May 2015 | |
Robust Investment Management with Uncertainty in Fund Managers’ Asset Allocation∗
1 Associate, Quantitative Research and
Analytics, JP Morgan, New
York, NY,
USA.
This email address is being protected from spambots. You need JavaScript enabled to view it.
2 Visiting Associate Professor, M.I.T.
Sloan School of Management, Cambridge, MA, USA and Associate Professor, Lehigh
University, Department of Industrial and Systems Engineering,
Bethlehem, PA, USA.
This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
24
April
2014
Accepted:
10
March
2015
Abstract
We consider a problem where an investment manager must allocate an available budget among a set of fund managers, whose asset class allocations are not precisely known to the investment manager. In this paper, we propose a robust framework that takes into account the uncertainty stemming from the fund managers’ allocation, as well as the more traditional uncertainty due to uncertain asset class returns, in the context of manager selection and portfolio management when short sales are not allowed. A key application area is university endowments funds. We assume that only bounds on the fund managers’ holdings (expressed as fractions of the portfolio) are available, and fractions must sum to 1 for each fund manager. We define worst-case risk as the largest variance attainable by the investment manager’s portfolio over that uncertainty set. We propose two exact approaches (of different complexity) and a heuristic one to solve the problem efficiently. Numerical experiments suggest that our robust model provides better protection against risk than the nominal model when the fund managers’ allocations are not known precisely.
Mathematics Subject Classification: 90B50 / 90C90
Key words: Portfolio optimization / robust optimization / investment management
This research was done while the first author was a doctoral student at Lehigh University.
© EDP Sciences, ROADEF, SMAI 2015
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.
