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In the framework of risk management, for the study of the sensitivity of pricing and hedging in stochastic financial models to changes of parameters and to perturbations of the stock prices, we propose an error calculus which is an…

Probability · Mathematics 2008-12-02 Nicolas Bouleau

Many physical and mathematical models involve random fields in their input data. Examples are ordinary differential equations, partial differential equations and integro--differential equations with uncertainties in the coefficient…

Numerical Analysis · Mathematics 2021-12-07 Michael Griebel , Guanglian Li , Christian Rieger

The article is devoted to explicit one-step numerical methods with strong orders 1.0, 1.5, and 2.0 of convergence for Ito stochastic differential equations with multidimensional and non-commutative noise. For numerical modeling of iterated…

Probability · Mathematics 2022-09-13 Dmitriy F. Kuznetsov

We consider a stochastic version of the proximal point algorithm for optimization problems posed on a Hilbert space. A typical application of this is supervised learning. While the method is not new, it has not been extensively analyzed in…

Optimization and Control · Mathematics 2021-09-28 Monika Eisenmann , Tony Stillfjord , Måns Williamson

The numerical evaluation of statistics plays a crucial role in statistical physics and its applied fields. It is possible to evaluate the statistics for a stochastic differential equation with Gaussian white noise via the corresponding…

Numerical Analysis · Mathematics 2023-07-04 Jun Ohkubo

Diophantine approximation is traditionally the study of how well real numbers are approximated by rationals. We propose a model for studying Diophantine approximation in an arbitrary totally bounded metric space where the rationals are…

Number Theory · Mathematics 2024-03-20 Jonathan M. Fraser , Henna Koivusalo , Felipe A. Ramirez

Moment closure methods are widely used to analyze mathematical models. They are specifically geared toward derivation of approximations of moments of stochastic models, and of similar quantities in other models. The methods possess several…

Probability · Mathematics 2017-07-12 Ingemar Nåsell

We study linear function approximation in a finite basis under finite-precision arithmetic. In a highly non-orthogonal basis, certain directions are only weakly represented, so that rounding errors can significantly distort the effectively…

Numerical Analysis · Mathematics 2026-03-17 Astrid Herremans , Daan Huybrechs

The paper is concerned with the mathematical theory and numerical approximation of systems of partial differential equations (pde) of hyperbolic, pseudo-parabolic type. Some mathematical properties of the initial-boundary-value problem…

Numerical Analysis · Mathematics 2023-10-27 E. Abreu , E. Cuesta , A. Duran , W. Lambert

This paper focuses on systems of nonlinear second-order stochastic differential equations with multi-scales. The motivation for our study stems from mathematical physics and statistical mechanics, for examples, Langevin dynamics and…

Probability · Mathematics 2024-04-08 Nhu N. Nguyen , George Yin

Probabilistic numerics casts numerical tasks, such the numerical solution of differential equations, as inference problems to be solved. One approach is to model the unknown quantity of interest as a random variable, and to constrain this…

Numerical Analysis · Mathematics 2021-10-29 Onur Teymur , Christopher N. Foley , Philip G. Breen , Toni Karvonen , Chris. J. Oates

We develop a theoretical framework for studying numerical estimation of lower previsions, generally applicable to two-level Monte Carlo methods, importance sampling methods, and a wide range of other sampling methods one might devise. We…

Computation · Statistics 2018-07-12 Matthias C. M. Troffaes

Wave propagation problems have many applications in physics and engineering, and the stochastic effects are important in accurately modeling them due to the uncertainty of the media. This paper considers and analyzes a fully discrete finite…

Numerical Analysis · Mathematics 2021-06-30 Yukun Li , Shuonan Wu , Yulong Xing

This paper considers binomial approximation of continuous time stochastic processes. It is shown that, under some mild integrability conditions, a process can be approximated in mean square sense and in other strong metrics by binomial…

Computational Finance · Quantitative Finance 2015-02-09 Nikolai Dokuchaev

Stochastic approximation algorithms are iterative procedures which are used to approximate a target value in an environment where the target is unknown and direct observations are corrupted by noise. These algorithms are useful, for…

Logic in Computer Science · Computer Science 2022-08-10 Koundinya Vajjha , Barry Trager , Avraham Shinnar , Vasily Pestun

In this article, the existence and uniqueness about the solution for a class of stochastic fractional-order differential equation systems are investigated, where the fractional derivative is described in Caputo sense. The fractional…

Numerical Analysis · Mathematics 2016-11-24 Guang-an Zou , Bo Wang

This survey paper is a structured concise summary of four of our recent papers on the stochastic regularity of diffusions that are associated to regular strongly local (but not necessarily symmetric) Dirichlet forms. Here by stochastic…

Probability · Mathematics 2017-10-10 Jiyong Shin , Gerald Trutnau

The purpose of this work is the study of solution techniques for problems involving fractional powers of symmetric coercive elliptic operators in a bounded domain with Dirichlet boundary conditions. These operators can be realized as the…

Numerical Analysis · Mathematics 2013-02-05 Ricardo H. Nochetto , Enrique Otarola , Abner J. Salgado

We discuss the main stages of development of the error calculation since the beginning of XIX-th century by insisting on what prefigures the use of Dirichlet forms and emphasizing the mathematical properties that make the use of Dirichlet…

History and Overview · Mathematics 2014-01-14 Nicolas Bouleau

We propose a novel foundation for calculus that focuses on the notion of approximations while avoiding the use of limits altogether. Continuity is defined as approximation at a point, while differentiability is defined as approximation with…

History and Overview · Mathematics 2025-10-27 Michael P. Lamoureux , Matt Yedlin