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In this paper, we consider the explicit bound for the second-order approximation of the quadratic variation of a general fractional Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function $…

Probability · Mathematics 2021-06-18 Yong Chen , Zhen Ding , Ying Li

This paper studies the existence and uniqueness of solution of It\^o type stochastic differential equation $dx(t)=b(t, x(t), \om)dt+\si(t,x(t), \om) d B(t)$, where $B(t)$ is a fractional Brownian motion of Hurst parameter $H>1/2$ and…

Probability · Mathematics 2016-12-20 Yaozhong Hu

We present a numerical method for the approximation of solutions for the class of stochastic differential equations driven by Brownian motions which induce stochastic variation in fixed directions. This class of equations arises naturally…

Numerical Analysis · Mathematics 2010-06-15 David F. Anderson , Jonathan C. Mattingly

We consider a multidimensional Ito semimartingale regularly sampled on [0,t] at high frequency $1/\Delta_n$, with $\Delta_n$ going to zero. The goal of this paper is to provide an estimator for the integral over [0,t] of a given function of…

Statistics Theory · Mathematics 2013-08-14 Jean Jacod , Mathieu Rosenbaum

This article introduces a certain class of stochastic processes, which we suggest to call mild Ito processes, and a new - somehow mild - Ito type formula for such processes. Examples of mild Ito processes are mild solutions of SPDEs and…

Probability · Mathematics 2021-11-02 Giuseppe Da Prato , Arnulf Jentzen , Michael Roeckner

This paper proposes a novel multiscale estimator for the integrated volatility of an Ito process, in the presence of market microstructure noise (observation error). The multiscale structure of the observed process is represented…

Methodology · Statistics 2009-04-19 Sofia Olhede , Adam Sykulski , Grigorios Pavliotis

We discuss intrinsic noise effects in stochastic multiplicative-noise partial differential equations, which are qualitatively independent of the noise interpretation (Ito vs. Stratonovich), in particular in the context of noise-induced…

Statistical Mechanics · Physics 2009-11-10 O. Carrillo , M. Ibanes , J. Garcia-Ojalvo , J. Casademunt , J. M. Sancho

Bardina and Jolis [Stochastic process. Appl. 69 (1997) 83--109] prove an extension of It\^{o}'s formula for $F(X_t,t)$, where $F(x,t)$ has a locally square-integrable derivative in $x$ that satisfies a mild continuity condition in $t$ and…

Probability · Mathematics 2009-09-29 Xavier Bardina , Carles Rovira

We show that by using intuitive and accessible molecular features it is possible to predict the temperature-dependent second virial coefficient of organic and inorganic compounds using Gaussian process regression. In particular, we built a…

Chemical Physics · Physics 2021-02-24 Miruna T. Cretu , Jesús Pérez-Ríos

While absence of arbitrage in frictionless financial markets requires price processes to be semimartingales, non-semimartingales can be used to model prices in an arbitrage-free way, if proportional transaction costs are taken into account.…

Mathematical Finance · Quantitative Finance 2016-08-30 Christoph Czichowsky , Walter Schachermayer

In this paper, we demonstrate the simulation of fundamental solution for the parabolic equation by the relationship with Ito diffusion. The factorization and Monte Carlo methods of the fundamental solution are considered. With the fact that…

Methodology · Statistics 2014-07-07 Xinjun Gan , Gang Wei , Jie Zhang , Qi Zhang

We develop a stochastic calculus for processes which are built by convoluting a pure jump, zero expectation L\'{e}vy process with a Volterra-type kernel. This class of processes contains, for example, fractional L\'{e}vy processes as…

Probability · Mathematics 2008-12-18 Christian Bender , Tina Marquardt

Our simple but useful technique is using an integration by parts to split the stochastic convolution into two terms. We develop five applications for this technique. The first one is getting a uniform estimate of stochastic convolution of…

Probability · Mathematics 2012-01-24 Lihu Xu

Using the recently developed covariant Ito-Langevin dynamics, we develop a non-equilibrium thermodynamic theory for small systems coupled to multiplicative noises. The theory is based on Ito-calculus, and is fully covariant under…

Statistical Mechanics · Physics 2022-08-16 Mingnan Ding , Xiangjun Xing

The critical behaviour of systems belonging to the three-dimensional Ising universality class is studied theoretically using the collective variables (CV) method. The partition function of a one-component spin system is calculated by the…

Statistical Mechanics · Physics 2012-12-27 I. V. Pylyuk , M. V. Ulyak

This paper introduces an efficient tensor-vector product technique for the rapid and accurate approximation of integral operators within physics-informed deep learning frameworks. Our approach leverages neural network architectures to…

Machine Learning · Computer Science 2024-09-04 Alireza Afzal Aghaei , Mahdi Movahedian Moghaddam , Kourosh Parand

We define a new model using a Hawkes process as a subordinator in a standard Brownian motion. We demonstrate that this Hawkes subordinated Brownian motion or more succinctly, variance-Hawkes process can be fit to 2018 and 2019 natural gas…

Mathematical Finance · Quantitative Finance 2024-10-14 Joshua McGillivray , Anatoliy Swishchuk

We study the existence and uniqueness of solutions to stochastic differential equations with Volterra processes driven by L\'evy noise. For this purpose, we study in detail smoothness properties of these processes. Special attention is…

Probability · Mathematics 2020-08-26 Giulia Di Nunno , Yuliya Mishura , Kostiantyn Ralchenko

In Chen and Zhou 2021, they consider an inference problem for an Ornstein-Uhlenbeck process driven by a general one-dimensional centered Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function…

Statistics Theory · Mathematics 2021-12-30 Yong Chen , Xiangmeng Gu , Ying Li

This paper deals with optimal combined singular and regular controls for stochastic Volterra integral equations, where the solution X^{u,\xi}(t)=X(t) is given by X(t) =\phi(t)+\int_{0}^{t}}b(t,s,X(s),u(s))…

Optimization and Control · Mathematics 2021-04-15 Nacira Agram , Saloua Labed , Bernt Øksendal , Samia Yakhlef