This volume examines the theory of fractional Brownian motion and other long-memory
processes. Interesting topics for PhD students and specialists in probability theory …

We combine Malliavin calculus with Stein's method, in order to derive explicit bounds in the
Gaussian and Gamma approximations of random variables in a fixed Wiener chaos of a …

Statistics for stochastic processes is rapidly develo**. It forms a branch of mathematical
sciences, spreading over theoretical statistics, probability theory, software development and …

Central and non-central limit theorems for weighted power variations of fractional Brownian
motion Page 1 www.imstat.org/aihp Annales de l’Institut Henri Poincaré - Probabilités et …

The authors of this paper study approximation methods for stochastic differential equations,
and point out a simple relation between the order of convergence in the pth mean and the …

In this article, we study the numerical approximation of stochastic differential equations
driven by a multidimensional fractional Brownian motion (fBm) with Hurst parameter greater …

For a stochastic differential equation (SDE) driven by a fractional Brownian motion (fBm) with
Hurst parameter H>12, it is known that the existing (naive) Euler scheme has the rate of …

This paper proposes consistent and asymptotically Gaussian estimators for the parameters
λ, σ and H of the discretely observed fractional Ornstein–Uhlenbeck process solution of the …

Fix ν> 0, denote by G (ν/2) a Gamma random variable with parameter ν/2 and let n≥ 2 be a
fixed even integer. Consider a sequence {F k} k≥ 1 of square integrable random variables …

Full article: Existence and Uniqueness of the Solution of Stochastic Differential Equation
Involving Wiener Process and Fractional Brownian Motion with Hurst Index H > 1/2 Skip to Main …