AbstractWe extend the Skorohod integral, allowing integration with respect to Gaussian processes that can be more irregular than any fractional Brownian motion. This is done by restricting the class of test random variables used to define Skorohod integrability. A detailed analysis of the size of this class is given; it is proved to be non-empty even for Gaussian processes which are not continuous on any closed interval. Despite the extreme irregularity of these stochastic integrators, the Skorohod integral is shown to be uniquely defined, and to be useful: an Ito formula is established; it is employed to derive a Tanaka formula for a corresponding local time; linear additive and multiplicative stochastic differential equations are solved; ...
This article gives an account on various aspects of stochastic calculus in the plane. Specifically, ...
Preprint enviat per a la seva publicació en una revista científica: Stochastics and Stochastic Repor...
In this Chapter, the basic concepts of stochastic integration are explained in a way that is readily...
We extend the Skorohod integral, allowing integration with respect to Gaussian processes that can be...
We define a Skorohod type anticipative stochastic integral that extends the Ito integral not only wi...
ABSTRACT. We give a fairly complete survey of the stochastic integration with respect to the fractio...
In this paper a stochastic calculus is given for the fractional Brownian motions that have the Hurst...
In this paper a stochastic calculus is given for the fractional Brownian motions that have the Hurst...
Stochastic analysis with respect to fractional Brownian motion. Fractional Brownian motion (fBM for ...
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
Abstract. We study Skorohod integral processes on Lévy spaces and we prove an equivalence between t...
This thesis deals with the stochastic integral with respect to Gaussian processes, which can be expr...
Stochastic Integrals Driven by Isonormal Gaussian Processes and Applications Master Thesis - Petr Čo...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
This article gives an account on various aspects of stochastic calculus in the plane. Specifically, ...
Preprint enviat per a la seva publicació en una revista científica: Stochastics and Stochastic Repor...
In this Chapter, the basic concepts of stochastic integration are explained in a way that is readily...
We extend the Skorohod integral, allowing integration with respect to Gaussian processes that can be...
We define a Skorohod type anticipative stochastic integral that extends the Ito integral not only wi...
ABSTRACT. We give a fairly complete survey of the stochastic integration with respect to the fractio...
In this paper a stochastic calculus is given for the fractional Brownian motions that have the Hurst...
In this paper a stochastic calculus is given for the fractional Brownian motions that have the Hurst...
Stochastic analysis with respect to fractional Brownian motion. Fractional Brownian motion (fBM for ...
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
Abstract. We study Skorohod integral processes on Lévy spaces and we prove an equivalence between t...
This thesis deals with the stochastic integral with respect to Gaussian processes, which can be expr...
Stochastic Integrals Driven by Isonormal Gaussian Processes and Applications Master Thesis - Petr Čo...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
This article gives an account on various aspects of stochastic calculus in the plane. Specifically, ...
Preprint enviat per a la seva publicació en una revista científica: Stochastics and Stochastic Repor...
In this Chapter, the basic concepts of stochastic integration are explained in a way that is readily...