[HTML][HTML] Numerical methods for portfolio selection with bounded constraints
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.
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.
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.
Elsevier
以上显示的是最相近的搜索结果。 查看全部搜索结果