New method optimizes insurance portfolios using neural networks.
problem Optimizing insurance portfolios using clustering.
method Neural networks to optimize model points for grouping contracts.
result Superiority of method compared to K-means clustering.
SAA method solves insurance portfolio optimization with CVaR constraints.
problem Optimal allocation under CVaR constraint in insurance.
method Sample Average Approximation (SAA) method applied to CVaR constrained portfolio optimization.
result Convergence of SAA method and solution uniqueness proved under mild assumptions.
Insurance firms use RL to optimize customer offers for desired target portfolios.
problem Optimizing insurance offers to achieve a desired customer portfolio.
method Developed a novel reinforcement learning algorithm.
result The RL algorithm outperforms traditional methods in a synthetic market.
Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.
problem Investment and insurance decisions under a model with nonlinear portfolio frictions and background risk.
method Dynamic programming approach to find optimality conditions.
result Agent can choose to assume, partially assume, or purchase total insurance against adverse jumps in wealth.
This study compares VaR-based portfolio insurance with CPPI in a regime-switching market.
problem Designing dynamic portfolio insurance strategies in a market with multiple regimes.
method Extends VaR-based portfolio insurance to a Markov-modulated regime-switching market, comparing it to CPPI.
result CPPI strategy generally offers better risk-return tradeoff and stability.
This study compares the largest claims from two insurance portfolios using stochastic orderings.
problem Comparing the largest claims from two heterogeneous insurance portfolios.
method Used various stochastic orderings and established sufficient conditions associated with model parameters.
result Established sufficient conditions for comparing the largest claims from two insurance portfolios.
Paper models cloud outages for cyber insurance stress-testing.
problem Cyber insurance portfolios' vulnerability to simultaneous cloud outages.
method Modeling and calibrating cloud-outage scenarios, measuring diversification.
result Cloud-outage diversification can protect against accumulation risk.
Neural networks improve life insurance solvency calculations.
problem Computational challenges in Monte Carlo simulations for life insurance solvency.
method Use of neural networks as a proxy model for risk-neutral pricing.
result Neural networks solve feature engineering and selection problems in replicating portfolios.
Study large deviations in life insurance portfolios without identical distributions.
problem Large deviations in life insurance portfolios with bounded losses and variances.
method Upper bound from standard large deviations, counterexample for full large deviation principle.
result Exponential bound for average loss exceeding a threshold.
New algorithm improves insurance company's asset allocation decisions.
problem Strategic asset allocation with multiple objectives (risk, return, solvency, distance to current portfolio).
method Exact multi-objective optimization algorithm incorporating four objectives.
result Significant improvement in portfolio quality and decision-making process.
Model quantifies cyber-attacks' impact on firms and insurers.
problem Impact of cyber-attacks on firms' revenues and insurers' portfolios.
method Stochastic SIR model coupled with granular firm growth model.
result Predicts insurer needs to compensate up to two days of revenue in a 100-day incident.
Method reconstructs hidden Markov chains from insurance data.
problem Recovering hidden Markov chains from incomplete insurance data.
method Neural architecture to explicitly provide transition probabilities.
result Neural model successfully validates decompression of insurance information.
The paper examines the unexpected losses and risk ratios for co-monotonic alternatives in large portfolios.
problem Understanding the unexpected losses and risk ratios for large portfolios with co-monotonic alternatives.
method Analyzes the asymptotic behavior of unexpected losses and risk ratios for co-monotonic alternatives using monotone cash-additive risk measures and Choquet insurance premia.
result Unexpected losses of large weighted portfolios are of order o(nλn), where λn is the average weight. In these notes, we present some methods and applications of large deviations to finance and insurance. We begin with the classical ruin problem related to the Cramer's theorem and give en extension to an insurance model with investment in stock market. We then describe how large deviation approximation and importance s…
Study optimal dividend strategies for insurers with natural catastrophe claims.
problem Maximizing dividends for a catastrophe insurer over its lifetime.
method Two-dimensional stochastic control problem, viscosity solutions, numerical approximation.
result Optimal dividend strategies identified for natural catastrophe insurers.
The paper analyzes optimal investment strategies for life insurance contracts using mean-variance optimization.
problem Optimal portfolio choice for equity holders in life insurance contracts.
method Mean-variance optimization, explicit formulas, Hamilton-Jacobi-Bellman equations, numerical analysis.
result Equity holders increase investment in risky assets during economic downturns.
We study an infinite-horizon optimal investment, consumption and insurance problem for an economic agent who consumes a perishable and a durable good. The agent trades in a risk-free asset, a risky asset, and a durable good whose price follows a correlated diffusion, while the stock of the durable good depreciates dete…
The study designs a green investment fund and a hedging strategy for insurance policies linked to it.
problem Hedging unit-linked life insurance policies with an environmentally sensitive investment fund.
method Developed a carbon-intensity-driven portfolio selection rule and a quadratic hedging approach.
result The hedging strategy minimizes the variance of hedging costs, as demonstrated through numerical analysis.
New method for insurance valuation combining hedging and risk minimization.
problem Current insurance valuation methods do not reflect regulatory risk measures.
method Two-step hedging procedure using generalised regression.
result The method produces portfolios neutral to risk measures like VaR or expectiles.
Cointegration helps insurers understand long-range mortality patterns.
problem Insurers struggle to detect long-range dependence in their mortality data.
method Cointegration techniques applied to mixed fractional Brownian motion (mfBm) to capture long-range dependence.
result Cointegration brings long-range dependence information from national mortality data to insurers' models.
Framework monitors insurance pricing models for drift and recalibration.
problem Maintaining predictive performance of pricing models in evolving insurance portfolios.
method Formalizes deviance loss and Murphy's score, studies Gini score, develops monitoring framework.
result Framework guides decisions on refitting or recalibrating pricing models.
New EPS insurance offers partial protection against superannuation losses.
problem Lack of efficient investment insurance for superannuation holders.
method Developed a new financial derivative, equity protection swap (EPS), and derived a fair pricing formula.
result EPS can be an efficient investment insurance tool for superannuation accounts.
Neural networks assess asset-liability risk over time.
problem Challenging valuation of portfolios with complex products.
method Neural network approach for conditional portfolio valuation.
result Effective risk assessment for banking and insurance portfolios.
Paper proposes a surrogate model for efficient experience rating in large insurance portfolios.
problem Inexpensive and transparent computation of Bayesian premiums for large insurance portfolios.
method Surrogate modeling approach using likelihood-based summary statistics.
result Reduced computational burden and provided a transparent way of computing Bayesian premiums.
We study a continuous-time asset-allocation problem for an insurance firm that backs up liabilities from multiple non-life business lines with underwriting profits and investment income. The insurance risks are captured via a multidimensional jump-diffusion process with a multivariate compound Poisson process with depe…
The paper analyzes log-optimal portfolios in markets with random time events.
problem Analyzing log-optimal portfolios in markets with random events.
method Examined a market model with two information flows, F and G, and addressed log-optimal portfolio existence and sensitivity.
result Identified necessary and sufficient conditions for log-optimal portfolio existence, types of risks induced by random time, and factors affecting sensitivity.
We consider the problem of seeking an optimal set of model points associated to a fixed portfolio of life insurance policies. Such an optimal set is characterized by minimizing a certain risk functional, which gauges the average discrepancy with the fixed portfolio in terms of the fluctuation of the interest rate term …
When an insurance note is also a derivative a serious problem arises because a derivative must be fulfilled immediately. This feature of derivatives prevents claims processing procedures that screen out ineligible claims. This, in turn, creates a perverse incentive for insured holders of notes to commit acts that resul…
Using an extended version of the credit risk model CreditRisk+, we develop a flexible framework with numerous applications amongst which we find stochastic mortality modelling, forecasting of death causes as well as profit and loss modelling of life insurance and annuity portfolios which can be used in (partial) intern…
We study the problem of portfolio insurance from the point of view of a fund manager, who guarantees to the investor that the portfolio value at maturity will be above a fixed threshold. If, at maturity, the portfolio value is below the guaranteed level, a third party will refund the investor up to the guarantee. In ex…
The paper calculates bonus values in complex insurance schemes.
problem Calculating bonus payments in multi-state with-profit life insurance.
method Combines financial risk simulation with insurance risk methods.
result Efficient numerical procedures for bonus calculation.
In this paper, we solve portfolio rebalancing problem when security returns are represented by uncertain variables considering transaction costs. The performance of the proposed model is studied using constant-proportion portfolio insurance (CPPI) as rebalancing strategy. Numerical results showed that uncertain paramet…
New optimal investment strategies for finance and insurance using Hawkes-based models.
problem Optimal investment strategies in finance and insurance for specific models.
method Solving Merton investment problems with Hawkes-based models.
result New optimal investment results for finance and insurance models.
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.
In this paper we investigate the local risk-minimization approach for a combined financial-insurance model where there are restrictions on the information available to the insurance company. In particular we assume that, at any time, the insurance company may observe the number of deaths from a specific portfolio of in…
Study optimal dividend and capital injection in insurance portfolios with self-exciting claim arrivals.
problem Optimal dividend and capital injection in insurance portfolios with Hawkes process claim arrivals.
method Analytical properties, explicit threshold, HJB variational inequality, finite-difference scheme, policy-gradient, actor-critic methods.
result Learned strategies closely match the PDE benchmark and remain stable across initial conditions.
Study on excess mortality in Germany during 2020-21.
problem Analyzing excess mortality during the pandemic in Germany.
method Empirical study using official death counts.
result Provided conclusions for insurance businesses.
In this paper we study the pricing and hedging problem of a portfolio of life insurance products under the benchmark approach, where the reference market is modelled as driven by a state variable following a polynomial diffusion on a compact state space. Such a model guarantees not only the positivity of the OIS short …
This paper studies a Value-at-Risk (VaR)-regulated optimal portfolio problem of the equity holders of a participating life insurance contract. In a setting with unhedgeable mortality risk and complete financial market, the optimal solution is given explicitly for contracts with mortality risk using a martingale approac…
Paper models demand and solvency for index insurance, combining traditional and measurable index-based coverage.
problem Reducing protection gaps for emerging risks.
method Develops a model for demand and solvency conditions, combining traditional and index-based insurance.
result Deduces a product that benefits from both traditional and index-based insurance approaches.
In the present paper we provide a two-step principal protection strategy obtained by combining a modification of the Constant Proportion Portfolio Insurance (CPPI) algorithm and a classical Option Based Portfolio Insurance (OBPI) mechanism. Such a novel approach consists in assuming that the percentage of wealth invest…
Variable Annuity (VA) products expose insurance companies to considerable risk because of the guarantees they provide to buyers of these products. Managing and hedging these risks requires insurers to find the value of key risk metrics for a large portfolio of VA products. In practice, many companies rely on nested Mon…
Study optimizes insurance liability cash flows with regulatory capital requirements.
problem Valuation of insurance liabilities under regulatory capital constraints.
method Multiple-prior optimal stopping theory applied to insurance liabilities, considering hypothetical transfer and repeated capital requirements.
result Proposes a valuation functional for non-replicable cash flows, incorporating a margin for regulatory capital considerations.
Paper introduces a new principle for fair redistribution of insurance surplus.
problem Fair redistribution of surplus in life insurance policies.
method Introduces ISU decomposition principle based on infinitesimal sequential updates.
result Existing heuristic formulas can be replicated as ISU decompositions.
Optimizes multi-period portfolios with tail-risk constraints using neural networks.
problem Maximizing expected return while managing tail-risk constraints over multiple periods.
method Recurrent neural network approach to approximate optimal policy.
result Validated in financial and insurance models, capturing long-term risk dynamics.
Compact formulas for evaluating insurance policies' risks.
problem Quantifying demographic risk in insurance portfolios.
method Cohort-based approach with market-consistent valuation.
result Formal closed formula for idiosyncratic risk (accidental mortality).
Study a risk model with tree-structured Poisson-Markov random field for rainfall events.
problem Dependence between rainfall frequencies in insurance portfolios.
method Tree-structured Markov random field with Poisson marginals.
result Asymptotic results for portfolio risk and risk allocation.