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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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48 results for Life Expectancy

Investigates optimal life insurance and annuity decisions in inflationary economies.

problem Optimal consumption and investment decisions in an inflationary economy with money illusion.
method Formulated as a random horizon utility maximization problem, derived optimal strategy.
result Money illusion increases life insurance demand for young adults and reduces annuity demand for retirees.

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 optimizes investment strategies with constraints for life-cycle models.

problem Maximizing consumption, death benefit, and wealth under trading constraints.
method Deep pricing kernel approach to solve constrained portfolio optimization.
result Individuals reduce consumption, insurance demand, and wealth due to constraints.

The determinants of the velocity of money have been examined based on life-cycle hypothesis. The velocity of money can be expressed by reciprocal of the average value of holding time which is defined as interval between participating exchanges for one unit of money. This expression indicates that the velocity is govern…

2005-07-21abs ↗pdf ↗

The paper evaluates joint life insurance risk under dependence uncertainty using copulas and convex risk measures.

problem Evaluating risk of joint life insurance products under uncertainty in dependence structure.
method Monotonicity of risk evaluation with concordance order, linear programming for bounds, and numerical analysis.
result Bounds for mean, Value-at-Risk, and Expected Shortfall computed using linear programs.

End-to-end deep learning detects emotions in real-life emergency calls.

problem Recognizing emotions in real-life emergency call center recordings.
method Used an end-to-end deep learning architecture trained on IEMOCAP and CEMO datasets.
result Obtained 45.6% Unweighted Accuracy Recall on CEMO with 4 classes, 76.9% on 2 classes (Anger, Neutral).

Bounds derived for contract values in life insurance with financial market interaction.

problem Incompleteness in life tables for modern insurance products.
method Derivation of upper and lower bounds for hybrid functionals of lifetime under different assumptions.
result Characterization of worst- and best-case contract values over compatible mortality processes.

Proposes a mixed pension system combining PAYG and funded contributions to address sustainability.

problem Sustainability of public pension systems due to declining birth rates and increasing life expectancy.
method Combines a classical PAYG scheme with a funded investment scheme to ensure financial sustainability.
result Individuals contribute to a funded part, making them active participants in addressing demographic risks.

Real life hedging in the Black-Scholes model must be imperfect and if the stock's drift is higher than the risk free rate, leads to a profit on average. Hence the option price is examined as a fair game agreement between the parties, based on expected payoffs and a simple measure of risk. The resulting prices result in…

2019-03-19abs ↗pdf ↗

The paper examines higher moments in insurance, focusing on coskewness and its impact on actuarial quantities.

problem The impact of higher-order moments on actuarial applications, particularly expected shortfall and life annuity valuation.
method Derives analytical bounds for mixed moments under unspecified dependence structure, applies copula-based mixture model.
result Coskewness and odd-order mixed moments exhibit a monotonic relationship with expected shortfall and annuity premiums.

Framework predicts remaining useful life of DSH subsystems under unknown failure modes.

problem Predicting remaining useful life of DSH subsystems with unknown failure modes.
method Unsupervised framework using mixture of Gaussian regressions and Expectation-Maximization algorithm.
result Improved prediction accuracy and interpretability of RUL.

Dynamic clustering for time series data with evolving memberships.

problem Clustering multivariate time series data with dynamic membership changes.
method Dynamic Linear Models and Dirichlet evolution for mixture weights, with Gibbs sampling and efficient point estimation methods.
result Efficient dynamic clustering of time series data with evolving memberships.

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e. decision-makers are bounded in their rationality. Here we experimentally tested the predic…

2016-10-06abs ↗pdf ↗

We determine how an individual can use life insurance to meet a bequest goal. We assume that the individual's consumption is met by an income, such as a pension, life annuity, or Social Security. Then, we consider the wealth that the individual wants to devote towards heirs (separate from any wealth related to the afor…

2014-02-21abs ↗pdf ↗

The paper revisits and applies FTAP to life insurance and annuities pricing.

problem Non-arbitrage pricing of life contingent assets in dynamic markets.
method Revisit FTAP, use martingale theory, apply FTAP to life insurance and annuities, clarify assumptions.
result Valuation formula for life contingent assets including life insurance policies and annuities.

Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is using the Expectation Maximization (EM) algorithm. This algorithm, however, can get trapped in local maxima. In this paper we explore a new appro…

2012-10-19abs ↗pdf ↗

The study examines how different interpolation methods affect the decomposition of life insurance surplus.

problem The impact of different interpolation methods on the decomposition of life insurance surplus.
method The study uses the IASU decomposition method to analyze the effects of different interpolation methods (Lee-Carter and linear) on the surplus decomposition.
result Lee-Carter and linear interpolation yield almost identical decompositions, while constant approximations result in different decompositions.

Novel approach models life events using causal discovery and survival analysis.

problem Modeling life event choices and occurrence from a probabilistic perspective.
method Bi-level problem formulation: causal discovery for life events graph, survival analysis for time-to-event modeling.
result Identification of causal relationships and factors influencing transition rates between life events.

Bayesian MS-VAR model for pricing equity-linked life insurance products.

problem Pricing and hedging equity-linked life insurance products on maximum of several assets.
method Introduces Bayesian Markov-Switching Vector Autoregressive (MS-VAR) process to model economic variables and insured's lifetime.
result Obtains net single premiums and hedging formulas for equity-linked life insurance products.

Optimizes capital structure for life insurance companies with surplus participation.

problem Determining the optimal participation rate in life insurance contracts.
method Adapted Leland's dynamic capital structure model to life insurance context.
result Optimal participation rate is highly sensitive to contract duration and tax rate.

This article focuses on the work of O. Chanel and G. Chichilnisky (2013) on the flaws of expected utility theory while assessing the value of life. Expected utility is a fundamental tool in decision theory. However, it does not fit with the experimental results when it comes to catastrophic outcomes ---see, for example…

2015-08-25abs ↗pdf ↗

This paper explores how machine learning can improve life insurance risk assessment.

problem Limited use of machine learning in life insurance due to statistical models' efficiency.
method Review and extension of traditional actuarial methodologies with machine learning techniques.
result Developed Python library for life insurance data, improving risk modeling.

LIFE framework improves model accuracy and interpretability.

problem Achieving high prediction accuracy and interpretability in neural networks.
method Three-step process: subset definition, feature creation, and linear model combination.
result LIFE consistently outperforms other models in prediction accuracy and interpretability.

We collect and analyze the data for working time, life expectancy, and the pair output and infrastructure of industrializing nations. During S-functional recovery from disaster the pair's time shifts yield 25 years for the infrastructure's physical lifetime. At G7 level the per capita outputs converge and the time shif…

2012-12-06abs ↗pdf ↗

The Allais and Ellsberg paradoxes show that the expected utility hypothesis and Savage's Sure-Thing Principle are violated in real life decisions. The popular explanation in terms of 'ambiguity aversion' is not completely accepted. On the other hand, we have recently introduced a notion of 'contextual risk' to mathemat…

2011-05-09abs ↗pdf ↗

Investigates timing and asset allocation for life insurance in uncertain financial planning.

problem Optimal timing and asset allocation for life insurance in uncertain financial planning.
method Analytical solutions using duality theory and free-boundary problems.
result Explicit expressions for value functions and optimal strategies in both scenarios.