Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,694 papers · 148 categories

Trend · papers per month

199398597796 · Jun 202019922001200920172026
48 results for reinsurance optimization

Study optimal reinsurance strategies in a game between insurer and two reinsurers.

problem Optimal reinsurance strategies in a competitive market.
method Stochastic game theory, Stackelberg model, Nash game, time-inconsistent control problem, extended Hamilton-Jacobi-Bellman equation.
result Equilibrium reinsurance strategies and premiums found for exponential claim size.

Study optimal investment-reinsurance strategies in equity-linked insurance products using Stackelberg game theory.

problem Optimizing investment and reinsurance strategies in equity-linked insurance products with capital guarantees.
method Modelled as a Stackelberg game where reinsurer acts as leader and insurer as follower, with general utility functions and power utility functions analyzed.
result Derive Stackelberg equilibrium for general utility functions and calculate it explicitly for power utility functions, finding reinsurer optimizes premium to incentivize maximal reinsurance purchase.

Study optimal reinsurance and investment to minimize drawdown risk.

problem Minimizing drawdown risk in a risk model with correlated insurance claims.
method Optimal reinsurance-investment strategy under expected value and variance premium principles, considering per-loss reinsurance and financial market investment.
result Closed-form expressions for optimal reinsurance-investment strategies and value functions.

This paper analyzes a game between insurer and reinsurer under ambiguity and risk aversion, optimizing reinsurance and investment strategies.

problem Optimizing reinsurance and investment strategies in a game between insurer and reinsurer under ambiguity and risk aversion.
method Stackelberg game, α\alpha-maxmin mean-variance criterion, Heston's stochastic volatility, Hamilton-Jacobi-Bellman equations, Riccati differential equations.
result Excess-of-loss reinsurance is optimal for the insurer, and the equilibrium strategies are determined by specific equations.

Optimal dividend strategy with irreversible reinsurance constraints.

problem Maximizing dividends while adhering to ratcheting and irreversible reinsurance constraints.
method Modeling dividend and reinsurance levels as nondecreasing processes, solving Hamilton-Jacobi-Bellman equation.
result Threshold strategy is optimal for maximizing discounted dividends until ruin.

Study optimal reinsurance pricing under model uncertainty for multiple insurers.

problem Optimal reinsurance pricing in the presence of multiple sources of model uncertainty.
method Solves a continuous-time Stackelberg game for general reinsurance contracts, considering entropy penalties and ambiguity in insurers' models.
result Reinsurer prices under a distortion of the barycentre of insurers' models, maximizing expected wealth with an entropy penalty.

In this paper we consider reinsurance or risk sharing from a macroeconomic point of view. Our aim is to find socially optimal reinsurance treaties. In our setting we assume that there are nn insurance companies each bearing a certain risk and one representative reinsurer. The optimization problem is to minimize the su…

2017-11-28abs ↗pdf ↗

Dynamic reinsurance minimizes insurer's cost of capital over time.

problem Minimizing insurer's cost of capital in a dynamic reinsurance setting.
method Dynamic extension of the static optimal reinsurance problem, viewed as a risk-sensitive Markov Decision Process.
result Existence of a stationary Markovian optimal reinsurance policy under an infinite planning horizon.

Optimizes reinsurance and investment strategies to minimize ruin probability.

problem Optimizing reinsurance and investment strategies to minimize ruin probability.
method Stochastic projected gradient method based on Malliavin calculus.
result Effectiveness of the proposed method demonstrated through numerical experiments.

Reinsurance can help life insurers maintain higher capital guarantees without losing utility.

problem Decreasing capital guarantees in life insurance products.
method Dynamic investment-reinsurance optimization problem with simultaneous Value-at-Risk and no-short-selling constraints. Introduced guarantee-equivalent utility gain for comparison.
result Optimally managed reinsurance allows insurers to offer higher capital guarantees without reducing expected utility.

The paper analyzes reinsurance strategies in peer-to-peer insurance schemes.

problem Strategic interaction between plan managers and reinsurers in P2P insurance.
method Develops two game-theoretic contract designs: Pareto and Bowley designs, deriving optimal contracts and analyzing their welfare effects.
result The Bowley design yields a unique optimal contract, while the Pareto design allows for multiple Pareto-optimal contracts.

This paper optimizes reinsurance contracts with belief differences between insurer and reinsurer.

problem Dynamic reinsurance design with heterogeneous beliefs under mean-variance framework.
method Modeling surplus process, applying partitioned domain optimization, solving HJB system.
result Optimal reinsurance contracts with belief heterogeneity are more complex than standard contracts.

Study optimal reinsurance contracts to prevent moral hazard under non-concave premium principles.

problem Preventing moral hazard in reinsurance contracts under non-concave premium principles.
method Develops optimal reinsurance contracts under a diffusion risk model with incentive compatibility constraints and extended distortion premium principles.
result An optimal reinsurance contract exists and is characterized by solving a double obstacle problem.

Optimal reinsurance contracts for multiple dependent risks are derived without specific dependency assumptions.

problem Finding optimal reinsurance contracts for multiple dependent risks without assuming their dependency structure.
method Assumes maximal expected utility criterion and independent negotiation of reinsurance for each risk. Derives optimality conditions and shows that under mild assumptions, optimal contracts are classical (non-randomized) type.
result Optimal reinsurance contracts exist and can be classical (non-randomized) type under mild assumptions.

A new insurance and reinsurance pricing scheme based on realized loss.

problem Determining fair and risk-adjusted insurance premiums.
method Performance-based variable premium scheme with random initial premium adjusted based on realized loss.
result The variable premium scheme reduces reinsurer's total risk exposure compared to expected-value premium.

Optimal reinsurance contracts designed for a continuum of risk types.

problem Designing optimal reinsurance contracts with a continuum of risk types.
method Principal-agent model, VaR at risk tolerance level, change of variables, univariate approach.
result Optimal reinsurance contracts are in stop-loss form, classifying agents into high and low risk groups.

The paper optimizes insurance strategies for two collaborating business lines.

problem Maximizing dividends and managing risk for two collaborating business lines.
method Closed-form solutions for optimal strategies, including dividend payout, reinsurance, and capital injection.
result Optimal strategies involve pure excess-of-loss reinsurance and transferring reserves to prevent ruin.

In this paper, we study an insurer's reinsurance-investment problem under a mean-variance criterion. We show that excess-loss is the unique equilibrium reinsurance strategy under a spectrally negative Lévy insurance model when the reinsurance premium is computed according to the expected value premium principle. Furthe…

2017-03-06abs ↗pdf ↗

Study optimal investment and reinsurance for insurance companies in a dynamic market model.

problem Optimal investment and reinsurance strategies for insurance companies in a regime-switching market model.
method Forward dynamic exponential utility, value function construction, proportional reinsurance optimization.
result Characterization of optimal investment strategy and proportional reinsurance level.

Two-layer model studies reinsurance contracts and competition between insurer and reinsurers.

problem Modeling and analyzing reinsurance contracts and competition between insurer and reinsurers.
method Two-layer stochastic game model with insurer negotiating with reinsurers, and reinsurers competing for business.
result Existence and uniqueness of equilibrium strategies for the insurer and reinsurers, characterized in semiclosed form.

This paper optimizes insurance reinsurance design under solvency constraints.

problem Optimizing risk transfer from an insurance company to a reinsurer under solvency constraints.
method Martingale method to derive optimal reinsurance design maximizing terminal value of surplus.
result Optimal reinsurance designs include a combination of proportional and stop-loss protection.

Investigates optimal insurance and reinsurance strategies with incomplete market information.

problem Optimal investment-reinsurance problem for insurance companies with unknown market risk.
method Converted the original problem into a filtered observation problem, applied stochastic control theory, and used Hamilton-Jacobi-Bellman equations.
result Explicit formulas for value function and optimal strategy provided.

The paper optimizes insurer's dividend, reinsurance, and capital injection strategies for two collaborating business lines.

problem Maximizing expected total dividend payments while managing risk and preventing ruin.
method Solving the problem using a closed-form value function for optimal strategies.
result Optimal strategies include threshold dividend payout, decreasing reinsured risk, and capital injection to prevent ruin.

In this paper we consider an optimal investment and reinsurance problem with partially unknown model parameters which are allowed to be learned. The model includes multiple business lines and dependence between them. The aim is to maximize the expected exponential utility of terminal wealth which is shown to imply a ro…

2020-01-30abs ↗pdf ↗

Study optimal investment-reinsurance strategy for insurers under random coefficients and jumps.

problem Optimal investment-reinsurance strategy for insurers with random coefficients and jumps.
method Solves backward stochastic differential equations with jumps under a convex cone constraint.
result Optimal strategy and value remain the same even with random coefficients and jumps.

Hybrid framework optimizes reinsurance using generative models and reinforcement learning.

problem Traditional reinsurance optimization relies on restrictive assumptions and static designs.
method Combines VAEs for joint distribution learning and PPO for dynamic treaty parameter adaptation.
result Hybrid method produces more resilient outcomes with higher surpluses and lower tail risk.

Optimal reinsurance strategy analyzed for dynamic risk model with self- and externally-excited jumps.

problem Optimal reinsurance in a dynamic contagion model with self-exciting and externally-exciting risks.
method Two methodologies: classical HJB approach and BSDE approach, focusing on Markovian setting.
result Comparison of self-exciting and externally-exciting risks highlights heightened risk from self-exciting component.

Optimal reinsurance and dividend strategy for insurance companies in a finite time.

problem Maximizing dividends while managing risk in a finite time horizon.
method Dynamic control problem with Hamilton-Jacobi-Bellman equation, penalty approximation method.
result Smoothness of the value function and comparison principle for its gradient.

Study optimizes insurance and investment strategies for risk-averse insurers under ambiguity.

problem Optimizing insurance and investment strategies for risk-averse insurers under ambiguity.
method Solves a coupled FBSDE to derive optimal strategies and value function.
result Optimal consumption, investment, and reinsurance strategies influenced by risk aversion and EIS.

Study optimal reinsurance and investment strategies under common shocks affecting financial and actuarial markets.

problem Maximizing expected exponential utility of terminal wealth in a company facing both ordinary and catastrophic claims.
method Modeling common shocks affecting financial and actuarial markets, using stochastic control and Hamilton-Jacobi-Bellman equations.
result Characterization of optimal reinsurance and investment strategies under common shock dependence.

The paper optimizes reinsurance under uncertain dependence among insurers.

problem Designing Pareto-optimal reinsurance contracts in a market with uncertain dependence.
method Robust optimization approach assuming known marginal distributions and unspecified dependence structure.
result Characterization of optimal indemnity schedules under worst-case scenario and derivation of optimal two-parameter layer contracts for independent risks.

Optimal reinsurance when Value at Risk and expected surplus is balanced through their ratio is studied, and it is demonstrated how results for risk-adjusted surplus can be utilized. Simplifications for large portfolios are derived, and this large-portfolio study suggests a new condition on the reinsurance pricing regim…

2019-12-09abs ↗pdf ↗

In this paper, we study a risk process modeled by a Brownian motion with drift (the diffusion approximation model). The insurance entity can purchase reinsurance to lower its risk and receive cash injections at discrete times to avoid ruin. Proportional reinsurance and excess-of-loss reinsurance are considered. The obj…

2011-12-17abs ↗pdf ↗

Paper proposes optimal investment and reinsurance strategies considering financial and insurance risks dependence.

problem Optimal investment and reinsurance strategies under dependent financial and insurance risks.
method Stochastic control approach to maximize expected exponential utility of terminal wealth.
result Minimal dependence between financial and insurance risks significantly impacts investment and reinsurance strategies.