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Walk dimension and function spaces on self-similar fractals

Katarzyna Pietruska-Pałuba (2009)

Banach Center Publications

We outline the construction of Brownian motion on certain self-similar fractals and introduce the notion of walk dimension. We then show how the probabilistic approach relates to the theory of function spaces on fractals.

Wasserstein metric and subordination

Philippe Clément, Wolfgang Desch (2008)

Studia Mathematica

Let ( X , d X ) , ( Ω , d Ω ) be complete separable metric spaces. Denote by (X) the space of probability measures on X, by W p the p-Wasserstein metric with some p ∈ [1,∞), and by p ( X ) the space of probability measures on X with finite Wasserstein distance from any point measure. Let f : Ω p ( X ) , ω f ω , be a Borel map such that f is a contraction from ( Ω , d Ω ) into ( p ( X ) , W p ) . Let ν₁,ν₂ be probability measures on Ω with W p ( ν , ν ) finite. On X we consider the subordinated measures μ i = Ω f ω d ν i ( ω ) . Then W p ( μ , μ ) W p ( ν , ν ) . As an application we show that the solution measures ϱ α ( t ) to the partial...

Wavelet analysis of the multivariate fractional brownian motion

Jean-François Coeurjolly, Pierre-Olivier Amblard, Sophie Achard (2013)

ESAIM: Probability and Statistics

The work developed in the paper concerns the multivariate fractional Brownian motion (mfBm) viewed through the lens of the wavelet transform. After recalling some basic properties on the mfBm, we calculate the correlation structure of its wavelet transform. We particularly study the asymptotic behaviour of the correlation, showing that if the analyzing wavelet has a sufficient number of null first order moments, the decomposition eliminates any possible long-range (inter)dependence. The cross-spectral...

Wavelet estimation of the long memory parameter for Hermite polynomial of gaussian processes

M. Clausel, F. Roueff, M. S. Taqqu, C. Tudor (2014)

ESAIM: Probability and Statistics

We consider stationary processes with long memory which are non-Gaussian and represented as Hermite polynomials of a Gaussian process. We focus on the corresponding wavelet coefficients and study the asymptotic behavior of the sum of their squares since this sum is often used for estimating the long–memory parameter. We show that the limit is not Gaussian but can be expressed using the non-Gaussian Rosenblatt process defined as a Wiener–Itô integral of order 2. This happens even if the original...

Wavelet method for option pricing under the two-asset Merton jump-diffusion model

Černá, Dana (2021)

Programs and Algorithms of Numerical Mathematics

This paper examines the pricing of two-asset European options under the Merton model represented by a nonstationary integro-differential equation with two state variables. For its numerical solution, the wavelet-Galerkin method combined with the Crank-Nicolson scheme is used. A drawback of most classical methods is the full structure of discretization matrices. In comparison, the wavelet method enables the approximation of discretization matrices with sparse matrices. Sparsity is essential for the...

Weak and strong moments of random vectors

Rafał Latała (2011)

Banach Center Publications

We discuss a conjecture about comparability of weak and strong moments of log-concave random vectors and show the conjectured inequality for unconditional vectors in normed spaces with a bounded cotype constant.

Weak averaging of stochastic evolution equations

Ivo Vrkoč (1995)

Mathematica Bohemica

A theorem on continuous dependence of solutions to stochastic evolution equations on coefficients is established, covering the classical averaging procedure for stochastic parabolic equations with rapidly oscillating both the drift and the diffusion term.

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