“…Since the process X n is a continuous semi-martingale, quiet general conditions, depending on the regularity of h, may be found in the literature. When h is càd-làg (right continuous with left limit), a sufficient condition for X n is to satisfy the so-called U.T criterium proved by Jakubowski, Mémin and Pagès (cf [14] or [16] for an equivalent formulation). Since X n is a finite variation process, according to the proposition 6.12 p.378 of [13], the U.T condition is equivalent to the tightness of the sequence (V ar(X n ) t ) n∈N * , for all t ∈ [0, 1], V ar(X n ) being the variation process given by…”
Recently, Nicolas Bouleau has proposed an extension of the Donsker's invariance principle in the framework of Dirichlet forms. He proves that an erroneous random walk of i.i.d random variables converges in Dirichlet law toward the Ornstein-Uhlenbeck error structure on the Wiener space [4]. The aim of this paper is to extend this result to some families of stochastic integrals.
“…Since the process X n is a continuous semi-martingale, quiet general conditions, depending on the regularity of h, may be found in the literature. When h is càd-làg (right continuous with left limit), a sufficient condition for X n is to satisfy the so-called U.T criterium proved by Jakubowski, Mémin and Pagès (cf [14] or [16] for an equivalent formulation). Since X n is a finite variation process, according to the proposition 6.12 p.378 of [13], the U.T condition is equivalent to the tightness of the sequence (V ar(X n ) t ) n∈N * , for all t ∈ [0, 1], V ar(X n ) being the variation process given by…”
Recently, Nicolas Bouleau has proposed an extension of the Donsker's invariance principle in the framework of Dirichlet forms. He proves that an erroneous random walk of i.i.d random variables converges in Dirichlet law toward the Ornstein-Uhlenbeck error structure on the Wiener space [4]. The aim of this paper is to extend this result to some families of stochastic integrals.
“…Therefore, from the condition 3 in Definition 2 we have that the total variations [Aij (X 6) IT are also uniformly bounded for each T. Now, after the reductions made, we easily see that in (9) Proof. The lemma follows, for example, from general results of Jakubowski-M6min-Pag~s [8]. See also [3], Lemma on p. 348, [13], Proposition 2.3.4.…”
“…Uniformly tight processes. We recall the definition of uniformly tight property (U T ) defined in Jakubowski, Mémin and Pagès (1989) [13]. Let Z n be a sequence of semimartingale, with the canonical decompositions…”
Motivated by the multilevel Monte Carlo method introduced by Giles [5], we study the asymptotic behavior of the normalized error process un,m(X n − X nm ) where X n and X nm are respectively Euler approximations with time steps 1/n and 1/nm of a given stochastic differential equation X driven by a pure jump Lévy process. In this paper, we prove that this normalized multilevel error converges to different non-trivial limiting processes with various sharp rates un,m depending on the behavior of the Lévy measure around zero. Our results are consistent with those of Jacod [9] obtained for the normalized error un(X n − X), as when letting m tends to infinity, we recover the same limiting processes. For the multilevel error, the proofs of the current paper are challenging since unlike [9] we need to deal with m dependent triangular arrays instead of one.
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