Survey on Multi-period Mean–Variance Portfolio Selection Model

Xiang Yu Cui, Jian Jun Gao, Xun Li, Yun Shi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Due to the non-separability of the variance term, the dynamic mean–variance (MV) portfolio optimization problem is inherently difficult to solve by dynamic programming. Li and Ng (Math Finance 10(3):387–406, 2000) and Zhou and Li (Appl Math Optim 42(1):19–33, 2000) develop the pre-committed optimal policy for such a problem using the embedding method. Following this line of research, researchers have extensively studied the MV portfolio selection model through the inclusion of more practical investment constraints, realistic market assumptions and various financial applications. As the principle of optimality no longer holds, the pre-committed policy suffers from the time-inconsistent issue, i.e., the optimal policy computed at the intermediate time t is not consistent with the optimal policy calculated at any time before time t. The time inconsistency of the dynamic MV model has become an important yet challenging research topic. This paper mainly focuses on the multi-period mean–variance (MMV) portfolio optimization problem, reviews the essential extensions and highlights the critical development of time-consistent policies.

Original languageEnglish
Pages (from-to)599-622
Number of pages24
JournalJournal of the Operations Research Society of China
Volume10
Issue number3
DOIs
Publication statusE-pub ahead of print - 5 Apr 2022

Keywords

  • Investment constraints
  • Multi-period mean–variance
  • Time inconsistency

ASJC Scopus subject areas

  • Mathematics(all)
  • Management Science and Operations Research
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Survey on Multi-period Mean–Variance Portfolio Selection Model'. Together they form a unique fingerprint.

Cite this