On Some non Asymptotic Bounds for the Euler Scheme

We obtain non asymptotic bounds for the Monte Carlo algorithm associated to the Euler discretization of some diffusion processes. The key tool is the Gaussian concentration satisfied by the density of the discretization scheme. This Gaussian concentration is derived from a Gaussian upper bound of the density of the scheme and a modification of the so-called "Herbst argument" used to prove Logarithmic Sobolev inequalities. We eventually establish a Gaussian lower bound for the density of the scheme that emphasizes the concentration is sharp.

[1]  S. Menozzi,et al.  Density estimates for a random noise propagating through a chain of differential equations , 2010 .

[2]  Y. Ollivier,et al.  CURVATURE, CONCENTRATION AND ERROR ESTIMATES FOR MARKOV CHAIN MONTE CARLO , 2009, 0904.1312.

[3]  Céline Labart,et al.  Sharp estimates for the convergence of the density of the Euler scheme in small time , 2008 .

[4]  S. Menozzi,et al.  Explicit parametrix and local limit theorems for some degenerate diffusion processes , 2008, 0802.2229.

[5]  J. Coron Control and Nonlinearity , 2007 .

[6]  Denis Talay,et al.  Concentration Inequalities for Euler Schemes , 2006 .

[7]  Enno Mammen,et al.  Edgeworth type expansions for Euler schemes for stochastic differential equations. , 2002, Monte Carlo Methods Appl..

[8]  S. Bobkov,et al.  Hypercontractivity of Hamilton-Jacobi equations , 2001 .

[9]  E. Mammen,et al.  Local limit theorems for transition densities of Markov chains converging to diffusions , 2000 .

[10]  C. Villani,et al.  Generalization of an Inequality by Talagrand and Links with the Logarithmic Sobolev Inequality , 2000 .

[11]  M. Ledoux Concentration of measure and logarithmic Sobolev inequalities , 1999 .

[12]  X. Mao,et al.  Stochastic Differential Equations and Applications , 1998 .

[13]  R. Caflisch Monte Carlo and quasi-Monte Carlo methods , 1998, Acta Numerica.

[14]  R. Bass Diffusions and Elliptic Operators , 1997 .

[15]  Denis Talay,et al.  The law of the Euler scheme for stochastic differential equations , 1996, Monte Carlo Methods Appl..

[16]  D. Nualart The Malliavin Calculus and Related Topics , 1995 .

[17]  S. Sheu Some Estimates of the Transition Density of a Nondegenerate Diffusion Markov Process , 1991 .

[18]  D. Talay,et al.  Expansion of the global error for numerical schemes solving stochastic differential equations , 1990 .

[19]  D. Stroock,et al.  Applications of the Malliavin calculus. II , 1985 .

[20]  B. Øksendal Stochastic Differential Equations , 1985 .

[21]  A. Friedman Partial Differential Equations of Parabolic Type , 1983 .

[22]  D. W. Stroock,et al.  Multidimensional Diffusion Processes , 1979 .

[23]  H. McKean,et al.  Curvature and the Eigenvalues of the Laplacian , 1967 .

[24]  A. Kolmogoroff,et al.  Zufallige Bewegungen (Zur Theorie der Brownschen Bewegung) , 1934 .