Dynamic portfolio choices by simulation-and-regression: Revisiting the issue of value function vs portfolio weight recursions

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• 作者：Michel Denault^a ; ^b ; ^{michel.denault@hec.ca} ; Jean-Guy Simonato^c ; ^{jean-guy.simonato@hec.ca}
• 关键词：Dynamic portfolio choices ; Portfolio optimization ; Approximate Dynamic Programming ; Least-squares Monte Carlo ; Simulation-and-regression
• 刊名：Computers & Operations Research
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：79
• 期：Complete
• 页码：174-189
• 全文大小：1926 K
• 卷排序：79

文摘

Dynamic portfolio choices are computed with a simulation-and-regression approach. Unlike the current literature, our approach does not use Taylor series. We examine and compare two computational alternatives within this framework. We find that both alternatives can achieve precise results, one being more robust.