Dimension Reduction in Stochastic Optimal Control

Dimension Reduction in Stochastic Optimal Control

Abstract

We introduce the general optimal stochastic control setting in the case of portfolio selection. We propose a two-step algorithm to solve the objective function. At the first step, we utilise the transformation from mean-variance portfolio selection to OLS regression, projecting the assets space into a single portfolio. Then we take the dimension-reduced control space into the single index dynamic programming problem which aims to solve a certain finite time horizon objective function.

Date
Event
Monash Econometrics Honours Project
Location
Melbourne, Australia
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Yangzhuoran Yang
PhD Student in Statistics