In a serry of papers we have presented an algorithm based on quantization for pricing American options. More generally this amounts to solve numerically an obstacle problem for some semi linear PDE^s. Our algorithm is based on a Monte Carlo method and so a statistical error comes on. In the present paper we study this error: we prove the Central Limit Theorem for the algorithm and we give evaluations of the variance.. The difficulty comes from the fact that the algorithm is not linear. On the other hand an interesting problem is to control the behaviour of the variance of the algorithm as the complexity increases.. It turns out that the variance does not blow up if the time discretization step and the space discretization step tend to zer
We develop a grid based numerical approach to solve a filtering problem, using results on optimal qu...
International audienceWe obtain a Central Limit Theorem for a general class of additive parameters (...
AbstractWe obtain a central limit theorem for a general class of additive parameters (costs, observa...
International audienceIn a series of papers we have presented an algorithm based on quantization for...
AbstractIn the paper Bally and Pagès (2000) an algorithm based on an optimal discrete quantization t...
This paper focuses on studying the multilevel Monte Carlo method recently introduced by Giles [8] an...
The numerical quantization method (see [B.P.1, B.P.2, B.P.P.1]) is a grid method which relies on the...
We consider numerical approximations to the quantile hedging price of a European claim in a nonlinea...
In problems of moderate dimensions, the quasi-Monte Carlo method usually provides better estimates t...
filters, ” refers to a general class of iterative algorithms that performs Monte Carlo approximation...
29 pagesWe propose a new approach to quantize the marginals of the discrete Euler diffusion proces...
We introduce a new approach for the numerical pricing of American options. The main idea is to choos...
We numerically compare some recent Monte Carlo algorithms devoted to the pricing and hedging America...
We prove an almost sure central limit theorem for some multidimensional stochastic algorithms used f...
This paper focuses on studying the multilevel Monte Carlo method recently introduced by Giles [8] an...
We develop a grid based numerical approach to solve a filtering problem, using results on optimal qu...
International audienceWe obtain a Central Limit Theorem for a general class of additive parameters (...
AbstractWe obtain a central limit theorem for a general class of additive parameters (costs, observa...
International audienceIn a series of papers we have presented an algorithm based on quantization for...
AbstractIn the paper Bally and Pagès (2000) an algorithm based on an optimal discrete quantization t...
This paper focuses on studying the multilevel Monte Carlo method recently introduced by Giles [8] an...
The numerical quantization method (see [B.P.1, B.P.2, B.P.P.1]) is a grid method which relies on the...
We consider numerical approximations to the quantile hedging price of a European claim in a nonlinea...
In problems of moderate dimensions, the quasi-Monte Carlo method usually provides better estimates t...
filters, ” refers to a general class of iterative algorithms that performs Monte Carlo approximation...
29 pagesWe propose a new approach to quantize the marginals of the discrete Euler diffusion proces...
We introduce a new approach for the numerical pricing of American options. The main idea is to choos...
We numerically compare some recent Monte Carlo algorithms devoted to the pricing and hedging America...
We prove an almost sure central limit theorem for some multidimensional stochastic algorithms used f...
This paper focuses on studying the multilevel Monte Carlo method recently introduced by Giles [8] an...
We develop a grid based numerical approach to solve a filtering problem, using results on optimal qu...
International audienceWe obtain a Central Limit Theorem for a general class of additive parameters (...
AbstractWe obtain a central limit theorem for a general class of additive parameters (costs, observa...