Achieving a Given Financial Goal with Optimal Deferred Term Insurance Purchasing Policy
Yuqi Li, Lihua Zhang

TL;DR
This paper develops optimal strategies for purchasing deferred term insurance to maximize the probability of achieving specific financial goals, considering both deterministic and stochastic financial environments with income, consumption, and risky investments.
Contribution
It introduces new control methods and solves complex differential equations to determine optimal insurance and investment strategies in a stochastic framework with time cutoffs.
Findings
Optimal strategies depend on time cutoffs m and n.
Deferred term insurance is preferable for those with limited financial resources.
Results extend previous models to include stochastic income and investment.
Abstract
This paper researches the problem of purchasing deferred term insurance in the context of financial planning to maximize the probability of achieving a personal financial goal. Specifically, our study starts from the perspective of hedging death risk and longevity risk, and considers the purchase of deferred term life insurance and deferred term pure endowment to achieve a given financial goal for the first time in both deterministic and stochastic framework. In particular, we consider income, consumption and risky investment in the stochastic framework, extending previous results in \cite{Bayraktar2016}. The time cutoff m and n make the work more difficult. However, by establishing new controls,``\emph{quasi-ideal value}" and``\emph{ideal value}", we solve the corresponding ordinary differential equations or stochastic differential equations, and give the specific expressions for the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInsurance and Financial Risk Management
