Browsing by Author "Riedle, Markus"

Now showing items 1-8 of 8

2001-10-19Buch

Affine Stochastic Differential Equations with Infinite Delay on Abstract Phase Spaces

Riedle, Markus
2005-11-02Buch

Delay differential equations driven by Lévy processes: stationarity and Feller properties

Reiß, Markus; Riedle, Markus; Gaans, Onno van

We consider a stochastic delay differential equation driven by a general Lévy process. Both, the drift and the noise term may depend on the past, but only the drift term is assumed to be linear. We show that the segment ...
2008-03-07Buch

Geometric Brownian Motion with delay

Riedle, Markus; Appleby, John A. D.; Mao, Xuerong

A geometric Brownian motion with delay is the solution of a stochastic differential equation where the drift and diffusion coefficient depend linearly on the past of the solution, i.e. a linear stochastic functional ...
2002-02-20Buch

Lyapunov Exponents for Linear Delay Equations in arbitrary Phase Spaces

Riedle, Markus
2005-01-01Buch

On Émery's inequality and a variation-of-constants formula

Riedle, Markus; Reiß, Markus; Gaans, Onno van

A generalization of Émery's inequality for stochastic integrals is shown for convolution integrals with respect to an arbitrary semimartingale. The inequality is used to prove existence and uniqueness of solutions of ...
2005-03-10Buch

Solutions of affine stochastic functional differential equations in the state space

Riedle, Markus

In this article we consider solutions of affine stochastic functional differential equations. The drift of these equations is specified by a functional defined on a general function space B which is only described ...
2006-08-02Buch

Solutions of stochastic delay equations in spaces of continuous functions

Riedle, Markus; Neerven, Jan van
2003-07-02Dissertation

Stochastische Differentialgleichungen mit unendlichem Gedächtnis

Riedle, Markus

Für einen R^d-wertigen stochastischen Prozess X auf R bezeichne X_t den Segmentprozess X_t:={X(t+u): u = 0. Es wird folgende affine stochastische Differentialgleichung mit unendlichem Gedächtnis betrachtet: dX(t)=L(X_t)dt ...