Worst-Case Investment and Reinsurance Optimization for an Insurer under Model Uncertainty
Joint Authors
Du, Ziping
Rong, Xi-min
Meng, Xiangbo
Zhang, Lidong
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
In this paper, we study optimal investment-reinsurance strategies for an insurer who faces model uncertainty.
The insurer is allowed to acquire new business and invest into a financial market which consists of one risk-free asset and one risky asset whose price process is modeled by a Geometric Brownian motion.
Minimizing the expected quadratic distance of the terminal wealth to a given benchmark under the “worst-case” scenario, we obtain the closed-form expressions of optimal strategies and the corresponding value function by solving the Hamilton-Jacobi-Bellman (HJB) equation.
Numerical examples are presented to show the impact of model parameters on the optimal strategies.
American Psychological Association (APA)
Meng, Xiangbo& Rong, Xi-min& Zhang, Lidong& Du, Ziping. 2016. Worst-Case Investment and Reinsurance Optimization for an Insurer under Model Uncertainty. Discrete Dynamics in Nature and Society،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1103642
Modern Language Association (MLA)
Meng, Xiangbo…[et al.]. Worst-Case Investment and Reinsurance Optimization for an Insurer under Model Uncertainty. Discrete Dynamics in Nature and Society No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1103642
American Medical Association (AMA)
Meng, Xiangbo& Rong, Xi-min& Zhang, Lidong& Du, Ziping. Worst-Case Investment and Reinsurance Optimization for an Insurer under Model Uncertainty. Discrete Dynamics in Nature and Society. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1103642
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1103642