Convergent Numerical Scheme for Singular Stochastic Control with State Constraints in a Portfolio Selection Problem

We consider a singular stochastic control problem with state constraints that arises in problems of optimal consumption and investment under transaction costs. Numerical approximations for the value function using the Markov chain approximation method of Kushner and Dupuis are studied. The main resu...

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Vydané v:	SIAM journal on control and optimization Ročník 45; číslo 6; s. 2169 - 2206
Hlavní autori:	Budhiraja, Amarjit, Ross, Kevin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2007
Predmet:	Applied sciences Approximation Bank accounts Costs Decision theory. Utility theory Exact sciences and technology Investments Investors Markov analysis Operational research and scientific management Operational research. Management science Portfolio theory Queuing theory. Traffic theory Scheduling, sequencing Stochastic control theory Utility functions Viscosity Solution uniqueness Markov decision Degenerate system Optimal policy State space Function approximation Boundary condition Modeling Uniqueness theorem Convergence Numerical approximation Markov chain Singular control Control constraint Portfolio selection Continuous control 90B35 Cost function Dirichlet problem 68M20 60K25 State constraint Consumption Neumann problem Probabilistic approach 60J70 free boundary problem Continuous function State space method Cost control Skorohod problem Selection problem 90B22 Value function Transaction cost Boundary value problem Hamilton Jacobi equation Approximation method Particular solution Optimal control Stochastic control Hamilton-Jacobi-Bellman equations Investment cost Portfolio management
ISSN:	0363-0129, 1095-7138
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