Equilibrium strategy for a multi-period weighted mean-variance portfolio selection in a Markov regime-switching market with uncertain time-horizon and a stochastic cash flow

Hao Ge, Xingyi Li, Xun Li and Zhongfei Li

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 6, 1797-1832

Abstract: This article considers a multi-period weighted mean-variance portfolio selection problem with uncertain time-horizon and a stochastic cash flow in a Markov regime-switching market. The random returns of risky assets and amount of the cash flow all depend on the states of a stochastic market which are assumed to follow a discrete-time Markov chain. Based on the conditional distribution of uncertain time-horizon caused by exogenous factors, we construct a more general mean-variance investment model. Within a game theoretic framework, we derive the equilibrium strategy and equilibrium value function in closed-form by applying backward induction approach. In addition, we show the equilibrium efficient frontier and discuss some degenerate cases. Finally, some numerical examples and sensitivity analysis are presented to illustrate equilibrium efficient frontiers and the effects of uncertain time-horizon on the equilibrium strategy and equilibrium efficient frontier as well as regime-switching and stochastic cash flow on the equilibrium efficient frontier.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2021.1939379 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:52:y:2023:i:6:p:1797-1832

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2021.1939379

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().