Unified pricing method for variable annuity guarantees using stochastic control.
problem Pricing variable annuity guarantees for retail investors.
method Optimal stochastic control framework, direct integration method with spline interpolation.
result Efficient numerical method for pricing variable annuity guarantees.
Variable annuities (VA) are popular insurance products. VAs provides the insured with a guaranteed accumulation rate on their premium at maturity. In addition, the insured may receive extra benefit if returns of underlying funds are high enough. Here we consider a special case of VA with high-water mark feature and Gua…
The paper offers a new model for variable annuities with surrender risk.
problem Modeling variable annuities with surrender risk and market consistency.
method Hybrid model with Lévy processes, time-inhomogeneous, and dependence between financial and surrender risks.
result Explicit analytical formulas and practical numerical procedures for variable annuity valuation.
In this paper we present a numerical valuation of variable annuities with combined Guaranteed Minimum Withdrawal Benefit (GMWB) and Guaranteed Minimum Death Benefit (GMDB) under optimal policyholder behaviour solved as an optimal stochastic control problem. This product simultaneously deals with financial risk, mortali…
Research examines GMIB and reset options in variable annuities.
problem Understanding the value and rationality of GMIB and reset options.
method Exploration of various parameters affecting GMIB value and calculation of critical future interest rates for reset option rationality.
result Insight into how future market performance and interest rates influence policyholder and insurer actions.
New pension design reduces volatility without guarantees.
problem Pension volatility and guarantees issues.
method Split premium, invest in funds, redistribute to smooth volatility.
result Maximizes total accumulated capital at retirement.
In this paper we explore an identity in distribution of hitting times of a finite variation process (Yor's process) and a diffusion process (geometric Brownian motion with affine drift), which arise from various applications in financial mathematics. As a result, we provide analytical solutions to the fair charge of va…
A large collection of financial contracts offering guaranteed minimum benefits are often posed as control problems, in which at any point in the solution domain, a control is able to take any one of an uncountable number of values from the admissible set. Often, such contracts specify that the holder exert control at a…
The study improves bounds on pseudo-Anosov maps and certifies minimum and accumulation points of normalized dilatations.
problem Understanding the set of normalized dilatations of fully-punctured pseudo-Anosov maps.
method Improving bounds on the number of tetrahedra in veering triangulations and using computational means.
result Certified that the minimum element of the set of normalized dilatations is μ2 and the minimum accumulation point is μ4. Paper assesses GMMB in VAs using FST for accurate net liability calculations.
problem Risk management of GMMB under stochastic mortality and regime-switching.
method Net liability model with FST algorithm for accurate numeric solutions.
result FST algorithm provides reliable results for net liability of GMMB.
Paper develops an efficient algorithm for pricing GMWB contracts under stochastic interest rates.
problem Valuation of Variable Annuities with Guaranteed Minimum Withdrawal Benefit under stochastic interest rates.
method Developed an efficient new algorithm for pricing GMWB contracts using backward recursion and high-order Gauss-Hermite quadrature.
result The new algorithm is significantly faster than finite difference or Monte Carlo methods for pricing GMWB contracts.
New method analyzes accumulation precision in deep learning networks.
problem Lack of precision analysis for accumulation in deep learning training.
method Statistical approach to analyze partial sum accumulations and derive equations for minimum required bits.
result Reduced accumulation precision can lead to loss of information and degraded network quality.
We propose a sampling scheme suitable for reducing a data set prior to selecting a hypothesis with minimum empirical risk. The sampling only considers a subset of the ultimate (unknown) hypothesis set, but can nonetheless guarantee that the final excess risk will compare favorably with utilizing the entire original dat…
Investigates optimal withdrawal strategies in VA contracts with tax and ratchet mechanisms.
problem Optimizing withdrawal strategies and behavior of policyholders in VA contracts with tax and ratchet mechanisms.
method Solving a backward dynamic programming problem to optimize cash flows from VA contracts, considering hybrid products and taxation effects.
result Tax-shielding effect of the cash fund enhances contract attractiveness, ratchet mechanism discourages early surrender, and cash fund discourages active withdrawals.
Insurance companies often include very long-term guarantees in participating life insurance products, which can turn out to be very valuable. Under a guaranteed annuity options (G.A.O), the insurer guarantees to convert a policyholder's accumulated funds to a life annuity at a fixed rated when the policy matures. Both …
An agent explores indefinitely in an environment with unlimited rewards.
problem Balancing exploration and exploitation in environments with unlimited rewards.
method Simple example of an environment with unbounded rewards and optimal agent behavior.
result An optimal agent always explores to maximize rewards, regardless of accumulated knowledge.
A variable annuity contract with Guaranteed Minimum Withdrawal Benefit (GMWB) promises to return the entire initial investment through cash withdrawals during the policy life plus the remaining account balance at maturity, regardless of the portfolio performance. Under the optimal withdrawal strategy of a policyholder,…
Minimum Description Length prevents overfitting in noisy data.
problem Learning from noisy data with overfitting risk.
method Minimum Description Length learning rule with tempered guarantees.
result Tempered agnostic finite sample learning guarantees and asymptotic behavior characterization.
The guaranteed minimum withdrawal benefit (GMWB) rider, as an add on to a variable annuity (VA), guarantees the return of premiums in the form of peri- odic withdrawals while allowing policyholders to participate fully in any market gains. GMWB riders represent an embedded option on the account value with a fee structu…
AdaX improves Adam by exponentially accumulating past gradients, leading to better performance in machine learning tasks.
problem Adam's fast convergence can lead to local minimums in non-convex problems.
method AdaX exponentially accumulates past gradients to adaptively tune the learning rate.
result AdaX outperforms Adam in various machine learning tasks, including computer vision and natural language processing.
We construct a binomial model for a guaranteed minimum withdrawal benefit (GMWB) rider to a variable annuity (VA) under optimal policyholder behaviour. The binomial model results in explicitly formulated perfect hedging strategies funded using only periodic fee income. We consider the separate perspectives of the insur…
In this paper, we study the price of Variable Annuity Guarantees, especially of Guaranteed Annuity Options (GAO) and Guaranteed Minimum Income Benefit (GMIB), and this in the settings of a derivative pricing model where the underlying spot (the fund) is locally governed by a geometric Brownian motion with local volatil…
A new robust PCA estimator combining M-estimators and minimum divergence estimators.
problem Adverse effect of outlying observations in PCA for high-dimensional data.
method Minimum density power divergence estimator combined with a computationally efficient algorithm.
result High breakdown guarantee regardless of data dimension with theoretical support and practical applications.
New method for joint MEG/EEG source imaging improves accuracy.
problem Joint MEG/EEG source imaging for group studies.
method Minimum Wasserstein Estimates (MWE) using Optimal Transport.
result MWE produces more accurate source localization than standard methods.
Paper provides a performance guarantee for spectral clustering.
problem Finding the global solution to the minimum ratio cut problem.
method Two-step spectral clustering method with a rounding step, analyzed using two-to-infinity norm perturbation bounds.
result Spectral clustering is guaranteed to output the global solution under certain conditions.
EKSS uses ensembles of KSS for subspace clustering with theoretical guarantees.
problem Subspace clustering with poor empirical performance and lack of theoretical guarantees.
method EKSS leverages ensembles of KSS via evidence accumulation clustering framework.
result EKSS achieves theoretical recovery guarantees and excellent empirical performance.
The use of absolute return volatility has many modelling benefits says John Cotter. An illustration is given for the market risk measure, minimum capital requirements.
A new lifelong online learning framework combining current and accumulated knowledge.
problem Continuous learning over tasks with limited data and unknown number of instances.
method Interactive learning algorithm combining current task information and accumulated knowledge.
result Algorithm can benefit from small cumulative error even with few interactions.
Paper compares two annuity pricing models and finds insurer underestimates value.
problem Pricing variable annuities with guaranteed benefits.
method Examines classical risk-neutral and benchmark approaches.
result Insurer underestimates contract value under dynamic withdrawal strategy.
Pension benefits valuation with Florida second election and DB Underpin options.
problem Valuation of hybrid pension benefits with embedded options.
method Arbitrage-free pricing methodology to value Bermudan options.
result Illustrates the difference between FSE, DB Underpin, and Bermudan DB Underpin options.
Paper tackles Byzantine resilience in distributed multi-task learning.
problem Resilience of distributed algorithms in the presence of Byzantine agents.
method Online weight assignment rule based on accumulated loss and filtering.
result Aggregation with proposed weight assignment rule improves expected regret.
Pension benefits in rural China lead to cognitive decline among the elderly.
problem Cognitive decline in late adulthood among rural Chinese elderly.
method Examined the effects of a new pension scheme on cognitive performance.
result Pension benefits negatively impact cognitive functioning, particularly delayed recall.
Novel optimizer mitigates instability in asynchronous data parallel optimization.
problem Instability in asynchronous data parallel optimization.
method Pushes a normalized sequence of first-order gradients to a parameter server.
result Achieves better convergence rate compared to other optimizers.
Wide neural networks with asymmetrical node scaling converge globally and learn features.
problem Global convergence and feature learning in over-parameterised shallow networks.
method Gradient-based optimisation of wide, shallow neural networks with asymmetrical node scaling.
result Gradient flow and gradient descent converge to a global minimum and learn features, unlike in the NTK parameterisation.
The study examines VIX-linked fees for GMWBs using explicit solution simulation methods.
problem Decreasing the sensitivity of insurer's liability to volatility risk in GMWBs.
method Explicit weak solution for VA account value and Monte Carlo simulations.
result VIX-linked fees decrease the sensitivity of the insurer's liability to volatility risk.
Model of capital accumulation in a complex exchange space.
problem Capital accumulation dynamics in heterogeneous producer-consumer systems.
method Statistical field theory approach to analyze interactions and dynamics.
result Capital accumulation and agent position in the exchange space are correlated.
Optimizes investment and consumption for post-retirement with minimum guarantee.
problem Maximizing final annuity with minimum guarantee during decumulation phase.
method Dynamic programming via Hamilton-Jacobi-Bellman (HJB) equation, finite difference method.
result Existence and uniqueness of classical solutions proved through dual transformation.
Improves likelihood-free inference by using a new sampling approach to avoid biased data collection.
problem Efficient Bayesian inference without likelihood evaluation for real-world datasets.
method Introduces Neural Proposal (NP) to sample simulation inputs i.i.d. for unbiased posterior inference.
result Demonstrates improved performance, especially for multi-modal posteriors, through experiments.
FetchSGD reduces communication in federated learning with sketching.
problem Communication bottlenecks and convergence issues in federated learning.
method FetchSGD uses Count Sketch to compress and merge model updates efficiently.
result FetchSGD achieves high compression rates and good convergence without sparse client participation.
DFOP learns online without knowing distribution changes.
problem Learning with changing distributions and limited data scans.
method Distribution-free one-pass learning approach.
result Estimate error decreases until convergence with high probability.
The paper studies variable annuity benefits using exponential functionals of Levy processes.
problem Modeling equity returns with a Levy process to better fit market features.
method Uses exponential functionals of a Levy process to compute the distribution of variable annuity guaranteed benefits.
result Explicitly computes the distribution of certain exponential functionals.
This paper improves indoor positioning accuracy by deploying reference nodes to ensure Line-of-Sight.
problem Systematic bias errors in indoor positioning due to non-LoS propagation.
method Model indoor service area as a graph, partition into cliques for reference nodes, set minimum distance and angle parameters.
result Guaranteed LoS to reference nodes improves indoor positioning accuracy and precision.
Study of participating policies with guaranteed minimum interest rate and surrender option.
problem Analyzing the value and optimal surrender strategy of participating policies with minimum interest rate guarantee and surrender option.
method Probabilistic analysis using optimal stopping and free boundary theory.
result Identification of an optimal surrender strategy involving stop-loss and too-good-to-persist boundaries.
New framework for DNN training guarantees convergence to global minimum.
problem Training deep neural networks to converge to global minimum.
method Reformulated minimization problem with recursive algorithmic framework, using bounded style assumptions.
result Convergence to an ε-(global) minimum with O(1/ε^3) gradient computations.
Combines CPPI and option-based strategy to ensure equity exposure.
problem Cash-in risk and equity market participation in CPPI.
method Two-step strategy: CPPI with guaranteed minimum equity exposure.
result Shows effectiveness through numerical analysis of option prices.
The paper analyzes GMWB annuities in low interest rate environments.
problem Valuation of GMWB annuities in low interest rate conditions.
method Dynamic programming and Hull-White interest rate model.
result Low interest rates increase the fair value of GMWB annuities.
Study shows SW distance estimators are consistent and asymptotically valid for generative models.
problem Theoretical guarantees for SW distance in generative models.
method Investigation of asymptotic properties of SW distance estimators.
result Asymptotic consistency and central limit theorem for SW distance estimators.
A new topic modeling method that minimizes topic simplex volume.
problem Topic modeling efficiency and accuracy.
method Reformulates LDA as minimizing topic simplex volume, uses convex relaxation and ADMM.
result Relaxed problem has same global minimum as original under assumptions.