Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/119209
Title: Optimal mean–variance portfolio selection under regime-switching-induced stock price shocks
Authors: Shi, X
Xu, ZQ 
Issue Date: Oct-2025
Source: Systems and control letters, Oct. 2025, v. 204, 106200
Abstract: In this paper, we investigate mean-variance (MV) portfolio selection problems with jumps in a regime-switching financial model. The novelty of our approach lies in allowing not only the market parameters — such as the interest rate, appreciation rate, volatility, and jump intensity — to depend on the market regime, but also in permitting stock prices to experience jumps when the market regime switches, in addition to the usual micro-level jumps. This modeling choice is motivated by empirical observations that stock prices often exhibit sharp declines when the market shifts from a ‘‘bullish’’ to a ‘‘bearish’’ regime, and vice versa. By employing the completion-of-squares technique, we derive the optimal portfolio strategy and the efficient frontier, both of which are characterized by three systems of multi-dimensional ordinary differential equations (ODEs). Among these, two systems are linear, while the first one is an 𝓁-dimensional, fully coupled, and highly nonlinear Riccati equation. In the absence of regime-switching-induced stock price shocks, these systems reduce to simple linear ODEs. Thus, the introduction of regime-switching-induced stock price shocks adds significant complexity and challenges to our model. Additionally, we explore the MV problem under a no-shorting constraint. In this case, the corresponding Riccati equation becomes a 2𝓁-dimensional, fully coupled, nonlinear ODE, for which we establish solvability. The solution is then used to explicitly express the optimal portfolio and the efficient frontier.
Keywords: Mean-variance
Multi-dimensional nonlinear ODEs
Multi-dimensional Riccati equation
No-shorting constraint
Regime-switching jump shocks
Publisher: Elsevier BV
Journal: Systems and control letters 
ISSN: 0167-6911
EISSN: 1872-7956
DOI: 10.1016/j.sysconle.2025.106200
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