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.
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The authors are very grateful to the Editor and two anonymous referees for their valuable comments and suggestions, which leads to a significant improvement of the work.
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Supported by the National Natural Science Foundation of China (Nos. 11701436, 72004174) and the Fundamental Research Funds for the Central Universities (WUT: 3120621545).
Proof of Theorem 3.2
Proof of Theorem 3.2
Let \((\pi (s), \kappa (s))\) be an admissible strategy. By conditions (1) and (2) in Definition 2.1, we have
for all \(t>s\). By the product rule and the chain rule for the Malliavin derivatives, we have
and
Then by conditions (5) and (6) in Definition 2.1, Lemma 3.1, the Fubini theorem and the equalities above, we can deduce that
Moreover, by conditions (5) and (6) in Definition 2.1 and the Fubini theorem, we have
From Eq. (1) and the equalities above, we obtain that
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Chen, F., Li, B. & Peng, X. Portfolio Selection and Risk Control for an Insurer With Uncertain Time Horizon and Partial Information in an Anticipating Environment. Methodol Comput Appl Probab 24, 635–659 (2022). https://doi.org/10.1007/s11009-022-09941-6
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DOI: https://doi.org/10.1007/s11009-022-09941-6