A Stochastic Programming Approach For Multi-Period Portfolio Optimization With Transaction Costs

Mehmet Can, Narela Bajram


This paper uses stochastic programming to solve multi-period investment problems. We combine the feature of asset return predictability with practically relevant constraints arising in a multi-period investment context. The objective is to maximize the expected utility of the returns the periods to balance the liabilities. 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 multi-period problems, we consider short-term decisions, and incorporate a solution for the long, subsequent steady-state period to account for end effects.

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DOI: http://dx.doi.org/10.21533/scjournal.v1i2.57


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Copyright (c) 2015 SouthEast Europe Journal of Soft Computing

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

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