A generalized bridge is a stochastic process that is conditioned on N linear functionals of its path. We consider two types of representations: orthogonal and canonical. The orthogonal representation is constructed from the entire path of the process. Thus, the future knowledge of the path is needed. In the canonical representation the filtrations of the bridge and the underlying process coincide. The canonical representation is provided for prediction-invertible Gaussian processes. All martingales are trivially prediction-invertible. A typical non-semimartingale example of a prediction-invertible Gaussian process is the fractional Brownian motion. We apply the canonical bridges to insider trading.© 2014 The Authors. Published by Elsevier B...
27 pagesLet G be a topological compact group acting on some space Y. We study a decomposition of Y-i...
We consider a class of stochastic processes containing the classical and well-studied class of squar...
We study the asymptotic behavior of a Gaussian process conditioned to n linear functionals of its pa...
AbstractA generalized bridge is a stochastic process that is conditioned on N linear functionals of ...
We define a generalized Brownian bridge and we provide some information about its filtration. Two de...
This thesis consists of a summary and five papers, dealing with the modeling of Gaussian bridges and...
AbstractWe give an exposition of Brownian motion and the Brownian bridge, both continuous and discre...
We observe that the probability distribution of the Brownian motion with drift −cx/(1−t) where c≠1 i...
Given a Markovian Brownian martingale Z, we build a process X which is a martingale in its own filtr...
The iterative simulation of the Brownian bridge is well known. In this article, we present a vectori...
In this article, we develop a new approach to functional quantization, which consists in discretizin...
The purpose of this paper is to get a canonical representation of Gaussian processes which are equiv...
We introduce "probabilistic" and "stochastic Hilbertian structures". These seem to be a suitable con...
minor changes, references addedSpectral decomposition of the covariance operator is one of the main ...
Educação Superior::Ciências Exatas e da Terra::MatemáticaA Brownian bridge is a continuous stochasti...
27 pagesLet G be a topological compact group acting on some space Y. We study a decomposition of Y-i...
We consider a class of stochastic processes containing the classical and well-studied class of squar...
We study the asymptotic behavior of a Gaussian process conditioned to n linear functionals of its pa...
AbstractA generalized bridge is a stochastic process that is conditioned on N linear functionals of ...
We define a generalized Brownian bridge and we provide some information about its filtration. Two de...
This thesis consists of a summary and five papers, dealing with the modeling of Gaussian bridges and...
AbstractWe give an exposition of Brownian motion and the Brownian bridge, both continuous and discre...
We observe that the probability distribution of the Brownian motion with drift −cx/(1−t) where c≠1 i...
Given a Markovian Brownian martingale Z, we build a process X which is a martingale in its own filtr...
The iterative simulation of the Brownian bridge is well known. In this article, we present a vectori...
In this article, we develop a new approach to functional quantization, which consists in discretizin...
The purpose of this paper is to get a canonical representation of Gaussian processes which are equiv...
We introduce "probabilistic" and "stochastic Hilbertian structures". These seem to be a suitable con...
minor changes, references addedSpectral decomposition of the covariance operator is one of the main ...
Educação Superior::Ciências Exatas e da Terra::MatemáticaA Brownian bridge is a continuous stochasti...
27 pagesLet G be a topological compact group acting on some space Y. We study a decomposition of Y-i...
We consider a class of stochastic processes containing the classical and well-studied class of squar...
We study the asymptotic behavior of a Gaussian process conditioned to n linear functionals of its pa...