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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.

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1234 · May 201019922001200920172026
48 results for Reinsurance

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.

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.

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 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.

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.

The paper analyzes reinsurance strategies in a competitive multi-agent system.

problem Strategic interactions and competitive behavior in multi-layer reinsurance chains.
method Stochastic differential games and non-zero-sum game models to characterize strategic interactions. Dynamic programming and game theory to derive equilibrium strategies.
result Intensified competition reduces safety loadings in reinsurance contracts.

The paper analyzes strategic interactions in a multi-agent reinsurance chain using game theory.

problem Strategic behavior and competition among insurers and reinsurers in a multi-layer reinsurance chain.
method Employed Stackelberg differential games and non-zero-sum game models to characterize strategic interactions. Used dynamic programming and game theory to derive equilibrium strategies for investment and reinsurance.
result Intensified competition leads to reduced safety loadings in reinsurance contracts.

Study on reinsurance decisions using mean-variance criterion with irreversible contracts.

problem Optimizing reinsurance premiums and contracts in a Stackelberg game with irreversible contracts.
method Unified singular control framework applied to both discrete and continuous time reinsurance contracts.
result A single once-for-all reinsurance contract is preferred over multiple contracts, and the signing time is crucial.

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.

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.

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 ↗

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.

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.

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.

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.

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.

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 ↗

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.

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.

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.

Reinsurance counterparty credit risk (RCCR) is the risk of a loss arising from the fact that a reinsurance company is unable to fulfill her contractual obligations towards the ceding insurer. RCCR is an important risk category for insurance companies which, so far, has been addressed mostly via qualitative approaches. …

2019-09-10abs ↗pdf ↗

Study of insurer games with model uncertainty in reinsurance and investment strategies.

problem Model uncertainty and competitive insurers' performance under worst-case scenarios.
method Formulated robust mean-field game for non-linear system, derived closed-form solutions.
result Relative concerns lead to new hedging terms in investment and reinsurance strategies.

The paper values reinsurance contracts for dynamic catastrophe claims without arbitrage.

problem Valuation of reinsurance contracts for dynamic catastrophe claims without arbitrage.
method Compound dynamic contagion process, Esscher transform, Monte Carlo simulation.
result Arbitrage-free premiums for catastrophe stop-loss reinsurance contracts.

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.

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.

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 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.

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.

We develop a model for contagion in reinsurance networks by which primary insurers' losses are spread through the network. Our model handles general reinsurance contracts, such as typical excess of loss contracts. We show that simpler models existing in the literature--namely proportional reinsurance--greatly underesti…

2018-05-30abs ↗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 ↗

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.

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.

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 and reinsurance strategy for insurers under random coefficients.

problem Optimal mean-variance investment-reinsurance problem for insurers under Cramér-Lundberg model with random coefficients.
method Reduced to a constrained stochastic linear-quadratic control problem with jumps, solved using BSDE techniques and SREs.
result Explicit efficient investment-reinsurance strategy and mean-variance frontier.