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In this article we develop a new methodology to prove weak approximation results for general stochastic differential equations. Instead of using a partial differential equation approach as is usually done for diffusions, the approach…

Probability · Mathematics 2016-08-16 Emmanuelle Clément , Arturo Kohatsu-Higa , Damien Lamberton

We prove a support theorem of the type of Stroock-Varadhan for solutions of stochastic variational inequalities.

Probability · Mathematics 2010-05-19 Jiagang Ren , Siyan Xu

Given a stochastic differential equation with path-dependent coefficients driven by a multidimensional Wiener process, we show that the support of the law of the solution is given by the image of the Cameron-Martin space under the flow of…

Probability · Mathematics 2019-09-05 Rama Cont , Alexander Kalinin

A convergence theorem for the continuous weak approximation of the solution of stochastic differential equations by general one step methods is proved, which is an extension of a theorem due to Milstein. As an application, uniform second…

Numerical Analysis · Mathematics 2013-03-19 Kristian Debrabant , Andreas Rößler

We apply the recently developed theory of symmetry of stochastic differential equations to a stochastic version of the logistic equation, obtaining an explicit integration, i.e. an explicit formula for the process in terms of any single…

Mathematical Physics · Physics 2019-05-14 Giuseppe Gaeta

In this paper, we study the existence of random periodic solutions for semilinear stochastic differential equations. We identify these as the solutions of coupled forward-backward infinite horizon stochastic integral equations in general…

Probability · Mathematics 2015-02-11 Chunrong Feng , Huaizhong Zhao , Bo Zhou

Multistage stochastic optimization problems are oftentimes formulated informally in a pathwise way. These are correct in a discrete setting and suitable when addressing computational challenges, for example. But the pathwise problem…

Optimization and Control · Mathematics 2021-02-23 Paul Dommel , Alois Pichler

We study a triple of stochastic processes: a Wiener process $W_t$, $t \geq 0$, its running maxima process $M_t=\sup \{W_s: s \in [0,t]\}$ and its running minima process $m_t=\inf \{W_s: s \in [0,t]\}$. We derive the analytical formulas for…

Probability · Mathematics 2024-11-05 Karol Dąbrowski , Piotr Jaworski

We present a discrete time stochastic volatility model in which the conditional distribution of the logreturns is a Variance-Gamma, that is a normal variance-mean mixture with Gamma mixing density. We assume that the Gamma mixing density is…

Pricing of Securities · Quantitative Finance 2014-05-29 Lorenzo Mercuri , Fabio Bellini

Stochastic differential equations for processes with values in Hilbert spaces are now largely used in the quantum theory of open systems. In this work we present a class of such equations and discuss their main properties; moreover, we…

funct-an · Mathematics 2007-05-23 Alberto Barchielli , Fabio Zucca

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

In this paper new analytical and numerical approaches to valuating path-dependent options of European type have been developed. The model of stochastic volatility as a basic model has been chosen. For European options we could improve the…

Pricing of Securities · Quantitative Finance 2010-09-24 Yu. A. Kuperin , P. A. Poloskov

This note is concerned with an important for modelling question of existence of solutions of stochastic partial differential equations as proper stochastic processes, rather than processes in the generalized sense. We consider a first order…

Probability · Mathematics 2007-05-23 K. Hamza , F. C. Klebaner

This article is devoted to the stochastic anticipating equations with the extended stochastic integral with respect to the Gaussian processes of a special type. In the particular cases the solutions of such an equations are the well-known…

Probability · Mathematics 2007-05-23 Andrey A Dorogovtsev

We prove a Stroock-Varadhan's type support theorem for a stochastic partial differential equation (SPDE) on the real line with a noise term driven by a cylindrical Wiener process on $L_2 (\mathbb{R})$. The main ingredients of the proof are…

Probability · Mathematics 2019-02-07 Timur Yastrzhembskiy

Investigate the stochastic dynamic non-linear system with the Wiener and the Poisson perturbations. For such systems we construct the program control with probability one, which allows this system to move on the given trajectory. In this…

Dynamical Systems · Mathematics 2012-01-17 Elena Karachanskaya

The goal of this paper is to define stochastic integrals and to solve stochastic differential equations for typical paths taking values in a possibly infinite dimensional separable Hilbert space without imposing any probabilistic structure.…

Probability · Mathematics 2019-09-30 Daniel Bartl , Michael Kupper , Ariel Neufeld

One introduces a new variational concept of solution for the stochastic differential equation $dX+A(t)X\,dt+\lambda X\,dt=X\,dW,$ $t\in(0,T)$; $X(0)=x$ in a real Hilbert space where $A(t)=\partial\varphi(t)$, $t\in(0,T)$, is a maximal…

Probability · Mathematics 2018-02-22 Viorel Barbu , Michael Röckner

This paper provides an existence-and-uniqueness theorem characterizing the stochastic integral with respect to a Wiener process. The integral is represented as a mapping from the space of measurable and adapted pathwise locally integrable…

Probability · Mathematics 2018-12-27 Lars Tyge Nielsen

A class of stochastic delay equations in Banach space $E$ driven by cylindrical Wiener process is studied. We investigate two concepts of solutions: weak and generalised strong, and give conditions under which they are equivalent. We…

Probability · Mathematics 2013-01-23 Mariusz Górajski