Numerical methods for portfolio selection with bounded constraints

G. Yin; Hanqing Jin; Zhuo Jin

doi:10.1016/j.cam.2009.08.055

Numerical methods for portfolio selection with bounded constraints

G. Yin^*, Hanqing Jin, Zhuo Jin

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

13 Citations (Scopus)

Abstract

This work develops an approximation procedure for portfolio selection with bounded constraints. Based on the Markov chain approximation techniques, numerical procedures are constructed for the utility optimization task. Under simple conditions, the convergence of the approximation sequences to the wealth process and the optimal utility function is established. Numerical examples are provided to illustrate the performance of the algorithms.

Original language	English
Pages (from-to)	564-581
Number of pages	18
Journal	Journal of Computational and Applied Mathematics
Volume	233
Issue number	2
DOIs	https://doi.org/10.1016/j.cam.2009.08.055
Publication status	Published - 15 Nov 2009
Externally published	Yes

Keywords

Bounded constraint
Markov chain approximation
Numerical method
Portfolio selection
Stochastic control

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10.1016/j.cam.2009.08.055

Cite this

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title = "Numerical methods for portfolio selection with bounded constraints",

abstract = "This work develops an approximation procedure for portfolio selection with bounded constraints. Based on the Markov chain approximation techniques, numerical procedures are constructed for the utility optimization task. Under simple conditions, the convergence of the approximation sequences to the wealth process and the optimal utility function is established. Numerical examples are provided to illustrate the performance of the algorithms.",

keywords = "Bounded constraint, Markov chain approximation, Numerical method, Portfolio selection, Stochastic control",

author = "G. Yin and Hanqing Jin and Zhuo Jin",

year = "2009",

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language = "English",

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T1 - Numerical methods for portfolio selection with bounded constraints

AU - Yin, G.

AU - Jin, Hanqing

AU - Jin, Zhuo

PY - 2009/11/15

Y1 - 2009/11/15

N2 - This work develops an approximation procedure for portfolio selection with bounded constraints. Based on the Markov chain approximation techniques, numerical procedures are constructed for the utility optimization task. Under simple conditions, the convergence of the approximation sequences to the wealth process and the optimal utility function is established. Numerical examples are provided to illustrate the performance of the algorithms.

AB - This work develops an approximation procedure for portfolio selection with bounded constraints. Based on the Markov chain approximation techniques, numerical procedures are constructed for the utility optimization task. Under simple conditions, the convergence of the approximation sequences to the wealth process and the optimal utility function is established. Numerical examples are provided to illustrate the performance of the algorithms.

KW - Bounded constraint

KW - Markov chain approximation

KW - Numerical method

KW - Portfolio selection

KW - Stochastic control

UR - http://www.scopus.com/inward/record.url?scp=69249232416&partnerID=8YFLogxK

U2 - 10.1016/j.cam.2009.08.055

DO - 10.1016/j.cam.2009.08.055

M3 - Article

AN - SCOPUS:69249232416

SN - 0377-0427

VL - 233

SP - 564

EP - 581

JO - Journal of Computational and Applied Mathematics

JF - Journal of Computational and Applied Mathematics

IS - 2

ER -

Numerical methods for portfolio selection with bounded constraints

Abstract

Keywords

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