A mixed integer programming model for multistage mean–variance post-tax optimization

In this paper, we introduce a mixed integer stochastic programming approach to mean–variance post-tax portfolio management. This approach takes into account of risk in a multistage setting and allows general withdrawals from original capital. The uncertainty on asset returns is specified as a scenar...

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Veröffentlicht in:	European journal of operational research Jg. 185; H. 2; S. 451 - 480
Hauptverfasser:	Osorio, Maria A., Gulpinar, Nalan, Rustem, Berc
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.03.2008 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Applied sciences Exact sciences and technology Integer programming Mathematical programming Mean–variance portfolio management Multistage stochastic mixed integer quadratic programming Operational research and scientific management Operational research. Management science Optimization Portfolio management Portfolio theory Post-tax optimization Quadratic programming Risk Risk theory. Actuarial science Stochastic models Studies Mean–variance portfolio management Multistage stochastic mixed integer quadratic programming Post-tax optimization Script Mean-variance portfolio management Probabilistic approach Mixed integer programming Tax Capital Diversification Modeling Optimization Stochastic programming Risk aversion Uncertain system Stock exchange Robustness Risk management Portfolio management
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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