Numerical Methods for Portfolio Selection with Bounded Constraints

Author: 

Jin, H
Jin, Z
Yin, G

Publication Date: 

November 2009

Journal: 

Journal of Computational and Applied Mathematics

Last Updated: 

2020-05-15T02:08:07.137+01:00

Issue: 

2

Volume: 

233

DOI: 

10.1016/j.cam.2009.08.055

page: 

564-581

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.

Symplectic id: 

196181

Download URL: 

Submitted to ORA: 

Not Submitted

Publication Type: 

Journal Article