Model predictive control of constrained Markovian jump nonlinear stochastic systems and portfolio optimization under market frictions
In this paper we consider MPC for a class of constrained discrete-time Markovian switching systems consisting of a family of nonlinear stochastic subsystems whose nonlinear stochastic term for a particular mode is described by its statistical properties. The additive nonlinearity of the subsystems i...
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| Published in | Automatica (Oxford) Vol. 87; pp. 61 - 68 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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01.01.2018
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| Abstract | In this paper we consider MPC for a class of constrained discrete-time Markovian switching systems consisting of a family of nonlinear stochastic subsystems whose nonlinear stochastic term for a particular mode is described by its statistical properties. The additive nonlinearity of the subsystems is allowed to contain state, input, and independent noise vectors. It is allowed so that hard constraints are imposed on the input manipulated variables. The results obtained are applied to the dynamic investment portfolio selection problem for a financial market with switching modes subject to hard constraints on trading amounts taking into account the presence of market frictions. Our approach is tested on a set of real data from the Russian Stock Exchange MICEX. |
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| AbstractList | In this paper we consider MPC for a class of constrained discrete-time Markovian switching systems consisting of a family of nonlinear stochastic subsystems whose nonlinear stochastic term for a particular mode is described by its statistical properties. The additive nonlinearity of the subsystems is allowed to contain state, input, and independent noise vectors. It is allowed so that hard constraints are imposed on the input manipulated variables. The results obtained are applied to the dynamic investment portfolio selection problem for a financial market with switching modes subject to hard constraints on trading amounts taking into account the presence of market frictions. Our approach is tested on a set of real data from the Russian Stock Exchange MICEX. |
| Author | Dombrovskii, Vladimir Obyedko, Tatiana Samorodova, Maria |
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| Cites_doi | 10.1007/s10957-013-0292-x 10.1016/j.ejor.2013.10.060 10.1016/j.automatica.2014.08.031 10.1016/j.automatica.2015.02.021 10.1016/j.orl.2014.04.008 10.1109/TAC.2004.824471 10.1016/j.automatica.2006.10.022 10.1109/TAC.1987.1104428 10.1016/0022-247X(74)90043-2 10.1134/S0005117911050079 10.1016/j.jempfin.2012.04.011 10.1111/jofi.12080 10.1023/A:1024730101068 10.1109/9.16432 10.1016/j.ifacol.2015.11.288 10.1016/j.automatica.2014.10.128 10.1109/ACC.2015.7171190 |
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| Keywords | Investment portfolio Model predictive control Markovian jumps Constraints Nonlinear stochastic systems |
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| SubjectTerms | Constraints Investment portfolio Markovian jumps Model predictive control Nonlinear stochastic systems |
| Title | Model predictive control of constrained Markovian jump nonlinear stochastic systems and portfolio optimization under market frictions |
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