Geyer, Alois, Hanke, Michael, Weissensteiner, Alex. 2009. A Stochastic Programming Approach for Multi-Period Portfolio Optimization. Computational Management Science 6 (2): 187-208.
BibTeX
Abstract
This paper extends previous work on the use of stochastic linear programming to solve life-cycle investment problems. We combine the feature of asset return predictability with practically relevant constraints arising in a life-cycle investment context. The objective is to maximize the expected utility of consumption over the lifetime and of bequest at the time of death of the investor. Asset returns and state variables follow a first-order vector auto-regression and the associated uncertainty is described by discrete scenario trees. To deal with the long time intervals involved in life-cycle problems we consider a few short-term decisions (to exploit any short-term return predictability), and incorporate a closed-form solution for the long, subsequent steady-state period to account for end effects.
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Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Journal article |
Journal | Computational Management Science |
WU-Journal-Rating new | VW-D |
Language | English |
Title | A Stochastic Programming Approach for Multi-Period Portfolio Optimization |
Volume | 6 |
Number | 2 |
Year | 2009 |
Page from | 187 |
Page to | 208 |
Reviewed? | Y |
URL | http://www.springerlink.com/content/b0r47t3044561173/fulltext.pdf |
Associations
- Projects
- Stochastic optimization of multi-period asset allocation problems
- People
- Geyer, Alois (Details)
- Hanke, Michael (Former researcher)
- External
- Weissensteiner, Alex (Universität Innsbruck, Austria)
- Organization
- Institute for Financial Research IN (Details)
- Research areas (ÖSTAT Classification 'Statistik Austria')
- 5323 Econometrics (Details)
- 5347 Operations research (Details)
- 5358 Corporate finances (Details)