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February 2011 Fractional Lévy-driven Ornstein–Uhlenbeck processes and stochastic differential equations
Holger Fink, Claudia Klüppelberg
Bernoulli 17(1): 484-506 (February 2011). DOI: 10.3150/10-BEJ281

Abstract

Using Riemann–Stieltjes methods for integrators of bounded $p$-variation we define a pathwise integral driven by a fractional Lévy process (FLP). To explicitly solve general fractional stochastic differential equations (SDEs) we introduce an Ornstein–Uhlenbeck model by a stochastic integral representation, where the driving stochastic process is an FLP. To achieve the convergence of improper integrals, the long-time behavior of FLPs is derived. This is sufficient to define the fractional Lévy–Ornstein–Uhlenbeck process (FLOUP) pathwise as an improper Riemann–Stieltjes integral. We show further that the FLOUP is the unique stationary solution of the corresponding Langevin equation. Furthermore, we calculate the autocovariance function and prove that its increments exhibit long-range dependence. Exploiting the Langevin equation, we consider SDEs driven by FLPs of bounded $p$-variation for $p<2$ and construct solutions using the corresponding FLOUP. Finally, we consider examples of such SDEs, including various state space transforms of the FLOUP and also fractional Lévy-driven Cox–Ingersoll–Ross (CIR) models.

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Holger Fink. Claudia Klüppelberg. "Fractional Lévy-driven Ornstein–Uhlenbeck processes and stochastic differential equations." Bernoulli 17 (1) 484 - 506, February 2011. https://doi.org/10.3150/10-BEJ281

Information

Published: February 2011
First available in Project Euclid: 8 February 2011

zbMATH: 1284.60080
MathSciNet: MR2798001
Digital Object Identifier: 10.3150/10-BEJ281

Keywords: $p$-variation , fractional integral equation , fractional Lévy process , fractional Lévy–Ornstein–Uhlenbeck process , long-range dependence , Riemann–Stieltjes integration , stationary solution to a fractional SDE , Stochastic differential equation

Rights: Copyright © 2011 Bernoulli Society for Mathematical Statistics and Probability

Vol.17 • No. 1 • February 2011
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