文章基本信息

标题：A Simulation Approach to Statistical Estimation of Multiperiod Optimal Portfolios
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作者：Hiroshi Shiraishi
期刊名称：Advances in Decision Sciences
印刷版ISSN：2090-3359
电子版ISSN：2090-3367
出版年度：2012
卷号：2012
DOI：10.1155/2012/341476
出版社：Hindawi Publishing Corporation
摘要：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.