Robust optimal excess-of-loss reinsurance and investment strategy for an insurer in a model with jumps
Danping Li,
Yan Zeng and
Hailiang Yang
Scandinavian Actuarial Journal, 2018, vol. 2018, issue 2, 145-171
Abstract:
This paper considers a robust optimal excess-of-loss reinsurance-investment problem in a model with jumps for an ambiguity-averse insurer (AAI), who worries about ambiguity and aims to develop a robust optimal reinsurance-investment strategy. The AAI’s surplus process is assumed to follow a diffusion model, which is an approximation of the classical risk model. The AAI is allowed to purchase excess-of-loss reinsurance and invest her surplus in a risk-free asset and a risky asset whose price is described by a jump-diffusion model. Under the criterion for maximizing the expected exponential utility of terminal wealth, optimal strategy and optimal value function are derived by applying the stochastic dynamic programming approach. Our model and results extend some of the existing results in the literature, and the economic implications of our findings are illustrated. Numerical examples show that considering ambiguity and reinsurance brings utility enhancements.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://hdl.handle.net/10.1080/03461238.2017.1309679 (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:sactxx:v:2018:y:2018:i:2:p:145-171
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/sact20
DOI: 10.1080/03461238.2017.1309679
Access Statistics for this article
Scandinavian Actuarial Journal is currently edited by Boualem Djehiche
More articles in Scandinavian Actuarial Journal from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().