A simulation approach to statistical estimation of multiperiod optimal portfolios
type: Item
instance of: scholarly article
title: A simulation approach to statistical estimation of multiperiod optimal portfolios
zbMATH Open document ID: 1244.91105
DOI: 10.1155/2012/341476
author: Hiroshi Shiraishi
published in: Advances in Decision Sciences
publication date: 2012-08-14T00:00:00Z
review text: Summary: This paper discusses a simulation-based method for solving discrete-time multiperiod portfolio choice problems under AR\((1)\) process. The method is applicable even if the distributions of return processes are unknown. We first generate simulation sample paths of the random returns by using AR bootstrap. Then, for each sample path and each investment time, we obtain an optimal portfolio estimator, which optimizes a constant relative risk aversion (CRRA) utility function. When an investor considers an optimal investment strategy with portfolio rebalancing, it is convenient to introduce a value function. The most important difference between single-period portfolio choice problems and multiperiod ones is that the value function is time dependent. Our method takes care of the time dependency by using bootstrapped sample paths. Numerical studies are provided to examine the validity of our method. The result shows the necessity to take care of the time dependency of the value function.
Mathematics Subject Classification ID: 91G70
Mathematics Subject Classification ID: 91G60
Mathematics Subject Classification ID: 91G10
zbMATH DE Number: 6065403
zbMATH Keywords: simulation
zbMATH Keywords: statistical estimation
zbMATH Keywords: multiperiod optimal portfolios
Wikidata QID: Q58697777
MaRDI profile type: Publication
OpenAlex ID: W2159674319
cites work: Q3574973
description: scientific article; zbMATH DE number 6065403