This webpage presents a selected series of articles related to the use of particle methods in Mathematical finance, including
Option pricing & Portfolio optimization
Filtering and hidden Markov models
Stochastic Sampling Models and Methods
This list of topics is clearly far from being exhaustive, and it is partially biased towards my work on stochastic particle models.
More references and links to this subject can be added on demand. This webpage also contains some articles on the particle and sequential Monte Carlo methodology,
and the performance analysis of these algorithms. The forthcoming book on numerical methods in Finance also contains new developments on particle
methods in risk analysis, option pricing, and sensibility measure computations
R. Carmona, P. Del Moral, P. Hu, N. Oudjane. Numerical Methods in Finance. Springer New York, Series : Proceeding in Mathematics, (460p.) (to appear 2012).
The software BIIPS is a general software developed by the INRIA team ALEA
for bayesian inference with interacting particle systems, a.k.a. Sequential Monte Carlo methods.
A demonstration of the BiiPS software for estimating the stochastic volatility of financial data can be found in
R. Carmona, P. Del Moral, P. Hu, N. Oudjane An introduction to particle methods in finance in Numerical Methods in Finance (43p.).
Springer New York, Series : Proceeding in Mathematics, (to appear 2012).
P. Del Moral, B. Rémillard, S. Rubenthaler. Monte Carlo approximations of american option that preserve monotonicity and convexity.
Numerical Methods in Finance (28p.). Springer New York, Series : Proceeding in Mathematics, (to appear 2012).