We introduce a decoupling method on the Wiener space to define a wide class of anisotropic Besov spaces. The decoupling method is based on a general distributional approach and not restricted to the Wiener space. The class ...
Geiss, Christel; Labart, Céline; Luoto, Antti(Cambridge University Press (CUP), 2020)
Let (Y, Z) denote the solution to a forward-backward stochastic differential equation (FBSDE). If one constructs a random walk from the underlying Brownian motion B by Skorokhod embedding, one can show -convergence of ...
In this paper, we study in the Markovian case the rate of convergence in Wasserstein distance when the solution to a BSDE is approximated by a solution to a BSDE driven by a scaled random walk as introduced in Briand, ...
We show that the comparison results for a backward SDE with jumps
established in Royer (Stoch. Process. Appl 116: 1358–1376, 2006) and Yin and
Mao (J. Math. Anal. Appl 346: 345–358, 2008) hold under more simplified ...
Vihola, Matti(Institute for Operations Research and the Management Sciences, 2018)
Multilevel Monte Carlo (MLMC) and recently proposed unbiased estimators are closely related. This connection is elaborated by presenting a new general class of unbiased estimators, which admits previous debiasing schemes ...
