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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.

169,341 papers · 148 categories

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18375573 · May 202619922001200920182026
48 results for exercise regions

The paper analyzes American options with time-varying caps, finding complex exercise regions and deriving option pricing formulas.

problem Valuation of American capped call options with time-varying caps, especially when the cap grows or decreases over time.
method Probabilistic arguments and local time, characterizing exercise boundaries through recursive integral equations and piecewise constant segments.
result General representation formulas for option prices, derived from exercise boundaries and local time of the underlying process.

This paper analyzes optimal stopping regions for American options with Poisson exercise opportunities.

problem Analyzing the optimal stopping regions for American options with Poisson exercise opportunities.
method Computing identities related to the first Poisson arrival time to an interval and applying them to the computation of the optimal strategies.
result Explicit expressions of the stopping and continuation regions and the value function are obtained.

Paper defines when early exercise of American options is optimal under negative rates.

problem Determining optimal exercise times for American options with negative interest rates.
method Developed a new integral equation to price options and find exercise boundaries under negative rates, using modified fixed point method.
result Successfully developed and validated a new algorithm for pricing American options under negative rates.

Study pricing of American put options with stochastic interest rate and finite maturity.

problem Pricing American put options with stochastic interest rate and finite maturity.
method Applied stochastic calculus and Ito's lemma to derive the option value's formula and optimal exercise boundary.
result Existence and parametrisation of the optimal exercise boundary for the Vasicek model.

Study negative discount rate effects on perpetual options in Lévy models.

problem Negative discount rate impacts perpetual American and Swing options in Lévy models.
method Analyze perpetual American and put options in exponential Lévy models with negative discount rate, identify critical continuation prices, and generalize to Swing type problems.
result Double continuation region arises in negative discount rate cases, identified by critical prices.

What are East Africa's industrial opportunities? In this article we explore this question by using the Product Space to study the productive structure of five south-east African countries: Kenya, Mozambique, Rwanda, Tanzania and Zambia. The Product Space is a network connecting products that tend to be exported by the …

2012-03-01abs ↗pdf ↗

Investigates optimal timing in skew Brownian motion with surprising directional impacts.

problem Timing of irreversible investments in skew Brownian motion.
method Analyzes optimal stopping problems with skew Brownian motion, proving waiting is optimal at skew points.
result Higher skewness increases incentives to wait and postpones optimal timing.

We use probabilistic methods to characterise time dependent optimal stopping boundaries in a problem of multiple optimal stopping on a finite time horizon. Motivated by financial applications we consider a payoff of immediate stopping of "put" type and the underlying dynamics follows a geometric Brownian motion. The op…

2014-07-25abs ↗pdf ↗

Investors often miss out on early exercise of American options with dividends, volatility, and jumps.

problem Investors suboptimal exercise of American call options on dividend-paying stocks.
method Used a fast numerical technique to analyze a large database of investor decisions and incorporated stochastic volatility and jumps in pricing models.
result Pricing models with stochastic volatility and jumps reduce the loss from suboptimal exercise by a quarter.

Game options study gradual exercise and cancellation with transaction costs.

problem Analyzing game options with gradual exercise and cancellation under proportional transaction costs.
method Developed algorithmic constructions for bid and ask prices, superhedging strategies, and optimal mixed stopping times.
result Increased flexibility in hedging leads to tighter bounds on option price.

Paper examines floating exercise boundaries for American options in time-inhomogeneous models.

problem Floating exercise boundaries in time-inhomogeneous models with negative interest rates or yields.
method Semi-analytical approach for pricing American options.
result Specialized pricing methodologies are required for models with floating exercise boundaries.

Optimizing option exercise policies based on variance optimal martingale measure can lead to unappealing results.

problem Optimizing American option exercise policies under the variance optimal martingale measure can result in unappealing policies.
method Optimizing option exercise policies under the variance optimal martingale measure, then anchoring to the resulting value of this policy.
result Optimizing option exercise policies based on the variance optimal martingale measure can lead to unappealing results.

NeuralCD diagnoses student proficiency in exercises using neural networks.

problem Capturing complex student-exercise interactions for accurate cognitive diagnosis.
method Proposes NeuralCD framework using neural networks to learn complex interactions between students and exercises, incorporating monotonicity for interpretability.
result Demonstrates effectiveness of NeuralCD framework on real-world datasets, achieving both accuracy and interpretability.

Closed-form solution found for American put option boundary.

problem Finding the optimal exercise boundary for American put options.
method Three models of stock price dynamics with time-dependent parameters, leading to a closed-form solution for the exercise boundary.
result Explicit closed-form solution for the optimal exercise boundary of American put options.

MEx dataset benchmarks HAR and multi-modal fusion for exercise quality.

problem Recognizing and evaluating exercise quality for Musculoskeletal Disorders patients.
method Multi-sensor, multi-modal dataset with four sensors (pressure mat, depth camera, accelerometers) for HAR and exercise quality assessment.
result Reference performance for each sensor identified, exposing their strengths and weaknesses.

Research analyzes public opinions on Twitter about diabetes, diet, exercise, and obesity.

problem Understanding public health opinions on social media.
method Developed a multi-component semantic and linguistic framework to collect and analyze Twitter data.
result Strongest correlation found between exercise and obesity; other notable correlations between diabetes and obesity, diet and obesity.

New pricing methods for αα-quantile and early-exercise options using Spitzer identities.

problem Pricing perpetual Bermudan and American options and αα-quantile options.
method Based on Spitzer identities for general Lévy processes and Wiener-Hopf method.
result Direct calculation of the optimal exercise barrier for early-exercise options.

This paper analyzes model risk in American put options using Heston volatility model.

problem Model risk in optimal exercise of American put options.
method Benchmark methodology of Hull and Suo [2002], Heston stochastic volatility model, numerical finite difference methods.
result Optimal exercise behavior is influenced by stochastic volatility dynamics and return-volatility correlation, creating model risk.

Optimal exercise boundary for put options with delivery lags identified.

problem Analyzing the optimal exercise time for American put options with delivery lags.
method Decomposing the option into a European put and a new American-style derivative, using free boundary techniques.
result The optimal exercise boundary exists and is a strictly increasing and smooth curve.

The paper presents a method for personalized exercise recommendations that improves learner skill gain.

problem Adapting to individual needs in large, diverse groups of learners in digital environments.
method Contextual Thompson Sampling to select exercises that advance learner skill.
result The method recommends exercises associated with greater skill improvement and adapts to learner differences.

Optimal exercise timing of stock options analyzed with varying information on drift change.

problem Analyzing optimal exercise timing of stock options with varying information on drift change.
method Rigorous mathematical analysis and numerical methods to solve optimal stopping problems.
result Characterization of optimal exercise boundaries and smooth pasting properties in both information scenarios.

Researchers find the optimal exercise time for American options using a specific type of diffusion process.

problem Finding the optimal time to exercise American options with a time-dependent Ornstein-Uhlenbeck process.
method Optimal stopping problem, probabilistic arguments, non-linear Volterra-type integral equation, Picard iteration algorithm.
result They derive a non-linear Volterra-type integral equation and prove the exercise boundary's Lipschitz continuity and differentiability almost everywhere.

RKT model improves knowledge tracing by considering exercise relations and student forget behavior.

problem Traditional KT models fail to consider both exercise relations and student forget behavior.
method RKT model uses relation-aware self-attention to incorporate exercise relations and student forget behavior.
result RKT model outperforms state-of-the-art KT methods on real-world datasets.

A deep learning framework assesses physical rehabilitation exercises.

problem Lack of versatile, robust, and practical assessment methods for rehabilitation exercises.
method Deep learning framework with metrics, scoring functions, and neural networks.
result First implementation of deep neural networks for rehabilitation performance assessment.

New framework values ESOs with multiple exercises and job termination risk.

problem Valuing ESOs with complex exercise patterns and job termination risk.
method Fourier transform, finite differences, and maturity randomization methods.
result Analytic formulae for ESO costs under various conditions.

New method uses Hermite polynomials for American option valuation.

problem Valuation of American options with complex jump-diffusion dynamics.
method Hermite polynomial expansions of transition density and early exercise premium.
result Converging approximations to true option prices and exercise boundaries.

Develops a real-time exercise recommendation system using deep learning.

problem Improving accuracy in exercise recommendation systems without user feedback.
method Deep recurrent neural network with attention mechanisms, real-time expert feedback.
result Improved accuracy in exercise recommendation system after real-time active learning.

The paper optimizes trading strategies for assets modeled by a randomized Brownian bridge.

problem Optimizing trading strategies for assets with uninformative noise and unknown terminal prices.
method Modeling asset price evolution with an exponential randomized Brownian bridge and solving for optimal trading strategies numerically.
result Disconnected continuation/exercise regions appear under certain prior distributions.

Study optimal stopping for variable annuity contracts with discontinuous rewards.

problem Optimal timing to surrender a variable annuity contract with guaranteed minimum benefit.
method Analytical study of an optimal stopping problem with a discontinuous reward function, considering general fee and surrender charge functions.
result Characterization of the surrender region and its interrelation with fee and surrender charge functions.

New method simplifies analysis of exercise timing for ambiguous integral option contracts.

problem Impact of ambiguity on optimal exercise timing of integral option contracts.
method Parameterized family of excessive functions generating supermartingales, simplifying multidimensional problem to one-dimensional static optimization.
result Value of optimal policy and worst case measure expressed in terms of these processes.

Researchers find a way to price American options without relying on specific asset price models.

problem Determining the upper bound on the price of American options under model uncertainty.
method Using martingale optimal transport problem to describe model uncertainty and proving that optimal exercise schemes must be nonrandomized under certain conditions.
result The price upper bound and its relaxed version coincide under suitable convexity conditions, removing the need for the model-free price upper bound to be nonrandomized.