Minimum variance importance sampling via Population Monte Carlo
R. Douc; A. Guillin; J.-M. Marin; C. P. Robert
ESAIM: Probability and Statistics (2007)
- Volume: 11, page 427-447
- ISSN: 1292-8100
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topDouc, R., et al. "Minimum variance importance sampling via Population Monte Carlo." ESAIM: Probability and Statistics 11 (2007): 427-447. <http://eudml.org/doc/250132>.
@article{Douc2007,
abstract = {
Variance reduction has always been a central issue in Monte Carlo experiments. Population Monte Carlo
can be used to this effect, in that a mixture of importance functions, called a D-kernel, can be iteratively
optimized to achieve the minimum asymptotic variance for a function of interest among all possible mixtures.
The implementation of this iterative scheme is illustrated for the computation of the price of a European
option in the Cox-Ingersoll-Ross model. A Central Limit theorem as well as moderate deviations
are established for the D-kernel Population Monte Carlo methodology.
},
author = {Douc, R., Guillin, A., Marin, J.-M., Robert, C. P.},
journal = {ESAIM: Probability and Statistics},
keywords = {Adaptivity;
Cox-Ingersoll-Ross model;
Euler scheme;
importance sampling;
mathematical finance;
mixtures;
moderate deviations;
population Monte Carlo;
variance reduction.; adaptivity; cox-ingersoll-Ross model; Euler scheme; importance sampling; mathematical finance; mixtures; moderate deviations; population Monte Carlo; variance reduction},
language = {eng},
month = {8},
pages = {427-447},
publisher = {EDP Sciences},
title = {Minimum variance importance sampling via Population Monte Carlo},
url = {http://eudml.org/doc/250132},
volume = {11},
year = {2007},
}
TY - JOUR
AU - Douc, R.
AU - Guillin, A.
AU - Marin, J.-M.
AU - Robert, C. P.
TI - Minimum variance importance sampling via Population Monte Carlo
JO - ESAIM: Probability and Statistics
DA - 2007/8//
PB - EDP Sciences
VL - 11
SP - 427
EP - 447
AB -
Variance reduction has always been a central issue in Monte Carlo experiments. Population Monte Carlo
can be used to this effect, in that a mixture of importance functions, called a D-kernel, can be iteratively
optimized to achieve the minimum asymptotic variance for a function of interest among all possible mixtures.
The implementation of this iterative scheme is illustrated for the computation of the price of a European
option in the Cox-Ingersoll-Ross model. A Central Limit theorem as well as moderate deviations
are established for the D-kernel Population Monte Carlo methodology.
LA - eng
KW - Adaptivity;
Cox-Ingersoll-Ross model;
Euler scheme;
importance sampling;
mathematical finance;
mixtures;
moderate deviations;
population Monte Carlo;
variance reduction.; adaptivity; cox-ingersoll-Ross model; Euler scheme; importance sampling; mathematical finance; mixtures; moderate deviations; population Monte Carlo; variance reduction
UR - http://eudml.org/doc/250132
ER -
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