Robust Dividend, Financing, and Reinsurance Strategies Under Model Uncertainty with Proportional Transaction Costs
Guohui Guan,
Lin He,
Zongxia Liang,
Yang Liu and
Litian Zhang
North American Actuarial Journal, 2024, vol. 28, issue 2, 261-284
Abstract:
This article studies the robust dividend, financing, and reinsurance strategies for an ambiguity aversion insurer (AAI) under model uncertainty. The AAI controls its liquid reserves by purchasing proportional reinsurance, paying dividends, and issuing new equity. We consider model uncertainty and suppose that the AAI is ambiguous about the liquid reserves process, which is described by a class of equivalent probability measures. The objective of the AAI is to maximize the expected present value of the dividend payouts minus the discounted costs of issuing new equity before bankruptcy under the worst-case scenario. A detailed proof of the verification theorem is shown for the robust singular-regular problem. We obtain the explicit solutions of the robust strategies, which are classified into three cases. Numerical results are also presented to show the impacts of the ambiguity aversion coefficient, and the transaction cost factor.
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/10920277.2023.2186430 (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:uaajxx:v:28:y:2024:i:2:p:261-284
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uaaj20
DOI: 10.1080/10920277.2023.2186430
Access Statistics for this article
North American Actuarial Journal is currently edited by Kathryn Baker
More articles in North American Actuarial Journal from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().