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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.

168,742 papers · 148 categories

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76151227302 · Jun 202019922001200920172026
48 results for stochastic discontinuities

Paper analyzes error in stochastic approximation for discontinuous functions.

problem Estimating expected error in discontinuous stochastic approximation.
method Uses finite differences and O(n1/5)O(n^{-1/5}) error estimate for discontinuous functions.
result Achieves error estimate of O(n1/5)O(n^{-1/5}) for discontinuous stochastic representation.

Study proves existence of equilibrium in incomplete economies with discontinuous volatility.

problem Existence of incomplete Radner equilibrium with nondegenerate endogenous volatility.
method Established existence of solution for Markovian quadratic BSDEs with discontinuous generators using unique continuation and backward uniqueness.
result Existence of incomplete Radner equilibrium with nondegenerate endogenous volatility.

Paper analyzes SGHMC for non-convex optimization with discontinuous gradients.

problem Training neural networks with ReLU activation.
method Non-asymptotic convergence analysis of SGHMC with discontinuous gradients.
result Explicit upper bounds for expected excess risk in non-convex optimization.

This work models overnight rates with jumps and discontinuities, extending classical short-rate models.

problem Capturing the jump behavior and discontinuities in overnight rates for accurate modeling.
method Developed a term structure modeling framework based on overnight rates, accommodating stochastic discontinuities.
result Simple specifications can capture the jump behavior of overnight rates, and explicit valuation formulas are provided.

New algorithm tackles optimization problems with discontinuous gradients in finance and insurance.

problem Optimization problems with discontinuous stochastic gradients in finance and insurance.
method Langevin dynamics based algorithm e-THε\varepsilonO POULA.
result Non-asymptotic error bounds and expected excess risk estimates for e-THε\varepsilonO POULA.

This paper tackles discontinuous neural networks for better approximation of piecewise continuous functions.

problem Limitation of neural networks in approximating piecewise continuous functions due to discontinuities.
method Proposes a decoupled two-step procedure to train a discontinuous deep neural network model.
result Provides approximation guarantees for the proposed model in piecewise continuous function spaces.

New method handles complex systems with discontinuous, heavy-tailed noise.

problem Handling discontinuous, heavy-tailed Lévy noise in stochastic systems.
method Developed nonlocal Kramers-Moyal formulas for SDEs with multiplicative Lévy noise.
result Validated framework for discovering interpretable SDE models from data.

New approach uses SGLD to minimize CVaR for portfolio weights.

problem Minimizing CVaR for portfolio weights with complete theoretical guarantees.
method Stochastic Gradient Langevin Dynamics (SGLD) with discontinuous updating.
result Theoretical guarantees for convergence in Wasserstein distances for convex and non-convex functions.

New method finds optimal learning rates for neural nets.

problem Finding optimal learning rates in stochastic neural networks.
method Gradient-only line searches using Non-negative Associative Gradient Projection Points (NN-GPPs).
result Learning rates can be reliably resolved as step sizes along search directions.

Estimates funding impact from an algorithmic relief rule, finding little effect on hospital activities.

problem Evaluating the impact of algorithmic policy decisions.
method Developed a treatment-effect estimator using algorithmic decisions as instruments.
result Funding from an algorithmic relief rule had little effect on COVID-19-related hospital activities.

We consider a market with fractional Brownian motion with stochastic integrals generated by the Riemann sums. We found that this market is arbitrage free if admissible strategies that are using observations with an arbitrarily small delay. Moreover, we found that this approach eliminates the discontinuity of the stocha…

2015-09-22abs ↗pdf ↗

Paper derives new option pricing formulas and approximations for a local volatility model with discontinuity.

problem Modeling extreme ATM skew in a local volatility model with discontinuity.
method Uses joint distribution of Skew Brownian motion and its functionals to derive option pricing formulas and approximations.
result Derives an approximation of option prices by Black-Scholes prices, simplifying skew behavior.

Proves nonemptyness of domains for specific group actions.

problem Nonemptyness of domains of proper discontinuity for Anosov groups of affine Lorentzian transformations.
method Proof of nonemptyness of domains of proper discontinuity.
result Proves nonemptyness of domains for Anosov groups of affine Lorentzian transformations.

TUSLA algorithm solves non-convex optimization problems with ReLU activations.

problem Non-convex stochastic optimization with super-linearly growing and discontinuous gradients.
method Non-asymptotic analysis of TUSLA algorithm for non-convex learning.
result TUSLA provides non-asymptotic error bounds in Wasserstein distances for non-convex learning.

DIF extends NF with stochastic discrete latent variables for better density estimation.

problem Improving density estimation with discontinuities and fine details.
method Discretely indexed flows as an extension of Normalizing Flows with stochastic latent variables.
result DIF inherit good computational behavior of NF and can capture distributions with discontinuities.

We consider the deformation of a discontinuous group acting on the Euclidean space by affine transformations. A distinguished feature here is that even a `small' deformation of a discrete subgroup may destroy proper discontinuity of its action. In order to understand the local structure of the deformation space of disc…

2006-03-14abs ↗pdf ↗

Cut-DeepONet handles discontinuities and sharp transitions in neural operators.

problem Neural operators struggle with discontinuities and sharp transitions in PDEs.
method Two-stage training framework that explicitly models discontinuities via a lifting strategy and input-dependent discontinuity prediction.
result Cut-DeepONet outperforms state-of-the-art methods on benchmark PDEs with low-resolution datasets.

New domains of discontinuity found for Anosov representations.

problem Understanding Anosov representations acting on homogeneous spaces.
method Constructing open domains of discontinuity for Anosov representations acting on specific homogeneous spaces.
result Describes the largest possible open domains of discontinuity for Zariski dense Anosov representations.

Unified reinforcement learning and stochastic processes with action-driven processes.

problem Combining reinforcement learning and stochastic processes for efficient control.
method Action-driven processes, leveraging control-as-inference, and minimizing Kullback-Leibler divergence.
result Action-driven processes unify reinforcement learning and stochastic processes, equivalent to maximum entropy reinforcement learning.

Study new symmetries in non-symmetric spaces and discontinuous groups.

problem Analyze symmetries in non-symmetric homogeneous spaces and discontinuous groups.
method Investigate discrete series, discontinuous groups, and analysis on pseudo-Riemannian spaces.
result New insights into symmetries of non-symmetric homogeneous spaces and discontinuous groups.

Improved multilevel scheme for value-at-risk computation.

problem Discontinuity in Heaviside function affects value-at-risk computation.
method Adaptive multilevel stochastic approximation to mitigate discontinuity.
result Best complexity improved to O(ε2lnε52\varepsilon^{-2}|\ln{\varepsilon}|^\frac52).

Extends nonlinear filtering to predictable jump times.

problem Filtering with jumps in both signal and observation, especially when jump times are known.
method Derive Kushner-Stratonovich and Zakai equations for predictable discontinuities.
result Extends classical nonlinear filtering results to a setting with predictable discontinuities.

Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not have the equation of motion describing the flows, or how they are affected by jumps. To this end, we introduce Neural Jump Stochastic Different…

2019-05-24abs ↗pdf ↗

This article gives an up-to-date account of the theory of discrete group actions on non-Riemannian homogeneous spaces. As an introduction of the motifs of this article, we begin by reviewing the current knowledge of possible global forms of pseudo-Riemannian manifolds with constant curvatures, and discuss what kind of …

2006-03-14abs ↗pdf ↗

This paper provides a new version of the condition of Di Nunno et al. (2003), Ankirchner and Imkeller (2005) and Biagini and \{O}ksendal (2005) ensuring the semimartingale property for a large class of continuous stochastic processes. Unlike our predecessors, we base our modeling framework on the concept of portfolio p…

2007-06-04abs ↗pdf ↗

This study improves credit risk management using advanced reinforcement learning.

problem Sub-optimal hedging of credit losses due to bid-ask costs and model limitations.
method Risk-averse stochastic-horizon reinforcement learning for dynamic risk management.
result Efficacy demonstrated through numerical study of a single FX forward contract portfolio.

New financial model with sandwiched volatility for option pricing.

problem Developing a new financial model for option pricing.
method Introducing a new model with stochastic volatility driven by a Gaussian Volterra process, ensuring the solution is sandwiched between two arbitrary Hölder continuous functions.
result Developed an algorithm for pricing options with discontinuous payoffs using Malliavin calculus.

Study proves rigid spectral properties of planets with metric discontinuities.

problem Establishing spectral rigidity for spherically symmetric planets with discontinuities.
method Novel trace formula applied to two wave types in spherically symmetric manifolds with boundary and interior interfaces.
result Spectral rigidity of spherically symmetric planets with discontinuities is proven.