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      • Department of Industrial Engineering
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      Robust scenario optimization based on downside-risk measure for multi-period portfolio selection

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      Author(s)
      Pınar, M. Ç.
      Date
      2007
      Source Title
      OR Spectrum
      Print ISSN
      0171-6468
      Electronic ISSN
      1436-6304
      Publisher
      Springer
      Volume
      29
      Issue
      2
      Pages
      295 - 309
      Language
      English
      Type
      Review
      Item Usage Stats
      237
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      Abstract
      We develop and test multistage portfolio selection models maximizing expected end-of-horizon wealth while minimizing one-sided deviation from a target wealth level. The trade-off between two objectives is controlled by means of a non-negative parameter as in Markowitz Mean-Variance portfolio theory. We use a piecewise-linear penalty function, leading to linear programming models and ensuring optimality of subsequent stage decisions. We adopt a simulated market model to randomly generate scenarios approximating the market stochasticity. We report results of rolling horizon simulation with two variants of the proposed models depending on the inclusion of transaction costs, and under different simulated stock market conditions. We compare our results with the usual stochastic programming models maximizing expected end-of-horizon portfolio value. The results indicate that the robust investment policies are indeed quite stable in the face of market risk while ensuring expected wealth levels quite similar to the competing expected value maximizing stochastic programming model at the expense of solving larger linear programs.
      Keywords
      Discrete scenario tree
      Downside risk
      Finance
      Multi-period portfolio selection
      Risk
      Stochastic programming
      Permalink
      http://hdl.handle.net/11693/38110
      Published Version (Please cite this version)
      http://dx.doi.org/10.1007/s00291-005-0023-2
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      • Department of Industrial Engineering 758
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