A parameterized method for optimal multi-period mean-variance portfolio selection with liability

Xun Li, Zhongfei Li, Xianping Wu, Haixiang Yao

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

1 Citation (Scopus)

Abstract

Big data is being generated by everything around us at all times. The massive amount and corresponding data of assets in the financial market naturally form a big data set. In this paper, we tackle the multi-period mean-variance portfolio of asset-liability management using the parameterized method addressed in Li et al. (SIAM J. Control Optim. 40:1540–1555, 2002) and the state variable transformation technique. By this simple yet efficient method, we derive the analytical optimal strategies and efficient frontiers accurately. A numerical example is presented to shed light on the results established in this work.
Original languageEnglish
Title of host publicationInternational Series in Operations Research and Management Science
Pages147-166
Number of pages20
DOIs
Publication statusPublished - 1 Jan 2017

Publication series

NameInternational Series in Operations Research and Management Science
Volume252
ISSN (Print)0884-8289

Keywords

  • Asset-liability management
  • Mean-variance formulation
  • Multi-period portfolio

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Strategy and Management
  • Management Science and Operations Research
  • Applied Mathematics

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