Portfolio Selection and Risk Control for an Insurer With Uncertain Time Horizon and Partial Information in an Anticipating Environment
Fenge Chen (),
Bing Li () and
Xingchun Peng ()
Additional contact information
Fenge Chen: Wuhan University of Technology
Bing Li: Wuhan University of Technology
Xingchun Peng: Wuhan University of Technology
Methodology and Computing in Applied Probability, 2022, vol. 24, issue 2, 635-659
Abstract:
Abstract This paper is devoted to the study of an optimal investment and risk control problem for an insurer. The risky asset process and the insurance liability process are governed by stochastic differential equations with jumps and anticipative parameters. The insurer can only get access to partial information about the financial market and the insurance business to make decisions. Taking into account endogenous and exogenous factors, we assume the time horizon is uncertain. With the aim of expected logarithmic utility maximization, we adopt the forward stochastic calculus and the Malliavin calculus to derive a characterization of the optimal strategy. In some particular cases, we obtain the optimal strategies in closed-form and get some new insights.
Keywords: Investment; Risk control; Uncertain time horizon; Partial information; Anticipative parameters; 97M30; 91G80; 93E20; 60H30 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s11009-022-09941-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:metcap:v:24:y:2022:i:2:d:10.1007_s11009-022-09941-6
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009
DOI: 10.1007/s11009-022-09941-6
Access Statistics for this article
Methodology and Computing in Applied Probability is currently edited by Joseph Glaz
More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().