Abstract
This paper studies a continuous-time mean-variance asset-liability management problem under the Heston model. Specifically, an asset-liability manager is allowed to invest in a risk-free asset and a risky asset whose price process is governed by the Heston model. By applying the Lagrange duality theorem and stochastic control theory, we derive the closed-form expressions of the efficient investment strategy and the efficient frontier. Moreover, we provide numerical experiments to analyze the sensitivity of the efficient frontier with respect to the relevant parameters in the Heston model.
Highlights
Asset-liability management (ALM) is essential for financial security systems such as banks, life insurance companies, property insurance companies and pension funds
2 Problem formulation we introduce the financial market and establish the optimal dynamic M–V ALM problem under the Heston model
5 Conclusions In this paper, we study the optimal dynamic M–V ALM problem under the Heston model
Summary
Asset-liability management (ALM) is essential for financial security systems such as banks, life insurance companies, property insurance companies and pension funds. Dynamic allocation strategies for mean–variance (M–V) ALM problems have been studied widely. These studies consider optimization problems of selecting optimal portfolios that can yield sufficient returns in compensating the corresponding liability. Based on the multi-period M–V framework, Leippold et al [3] investigate a multi-period ALM problem and derive explicit expressions for the efficient investment strategy and the efficient frontier. By using the stochastic linear-quadratic control theory, Chiu and Li [4] study a continuous-time ALM problem where the risky assets’ prices and the liability value are both governed by geometric Brownian motions. Xie et al [5] study a continuous-time ALM problem while the liability process is governed by a Brownian motion with drift. Chiu and Wong [12] investigate a M–V ALM prob-
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
