F. Black and M. Scholes, The Pricing of Options and Corporate Liabilities, Journal of Political Economy, vol.81, issue.3, pp.637-654, 1973.
DOI : 10.1086/260062

H. Gifford, K. Fong, and . Lin, A New Analytical Approach to Value at Risk, The Journal of Portfolio Management, vol.25, issue.5, pp.88-97, 1999.

P. Glasserman, Monte Carlo Methods in Financial Engineering, 2003.
DOI : 10.1007/978-0-387-21617-1

P. Glasserman, P. Heidelberger, and P. Shahabuddin, Variance Reduction Techniques for Estimating Value-at-Risk, Management Science, vol.46, issue.10, pp.1349-1364, 2000.
DOI : 10.1287/mnsc.46.10.1349.12274

P. Glasserman, P. Heidelberger, and P. Shahabuddin, Portfolio Value-at-Risk with Heavy-Tailed Risk Factors, Mathematical Finance, vol.1, issue.2, pp.239-269, 2002.
DOI : 10.1111/1467-9965.00141

J. Morio, R. Pastel, and F. L. Gland, An overview of importance splitting for rare event simulation, European Journal of Physics, vol.31, issue.5, pp.1295-1303, 2010.
DOI : 10.1088/0143-0807/31/5/028
URL : https://hal.archives-ouvertes.fr/hal-00911996

F. Cérou, P. Del-moral, T. Furon, and A. Guyader, Sequential Monte Carlo for rare event estimation, Statistics and Computing, vol.22, issue.4, pp.795-808, 2012.
DOI : 10.1007/s11222-011-9231-6

J. C. Cox and M. Rubinstein, Options Markets, 1985.

E. Steven and . Shreve, Stochastic Calculus for Finance II: Continuous-Time Models, 2004.

D. Lamberton and B. Lapeyre, Introduction to Stochastic Calculus Applied to Finance, 2007.

Y. Achdou and O. Pironneau, Computational Methods for Option Pricing, Society for Industrial and Applied Mathematic, 2005.
DOI : 10.1137/1.9780898717495
URL : https://hal.archives-ouvertes.fr/hal-00111740

R. C. Merton, Theory of rational option pricing, The Bell Journal of Economics and Management Science, pp.141-183, 1973.

F. A. Longstaff and E. S. Schwartz, Valuing American Options by Simulation: A Simple Least-Squares Approach, Review of Financial Studies, vol.14, issue.1, 2001.
DOI : 10.1093/rfs/14.1.113

J. A. Picazo, American Option Pricing: A Classification-Monte Carlo (CMC) Approach. Monte Carlo and Quasi-Monte Carlo Methods, Proceedings of a Conference Held at Hong Kong Baptist University, pp.422-433, 2000.

D. Viet and . Doan, Grid Computing for Monte Carlo Method based intensive calculations in financial derivative pricing applications, 2010.

M. Benguigui and F. Baude, Towards parallel and distributed computing on GPU for American basket option pricing, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings
DOI : 10.1109/CloudCom.2012.6427593
URL : https://hal.archives-ouvertes.fr/hal-00905450

D. Duffie and J. Pan, An Overview of Value at Risk, The Journal of Derivatives, vol.4, issue.3, 1997.
DOI : 10.3905/jod.1997.407971

I. N. Svetlozar and T. R. , Value at Risk: Recent Advances, pp.801-858, 2000.

R. F. Engel, Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, vol.50, issue.4, pp.987-1007, 1982.
DOI : 10.2307/1912773

E. Fournié, J. Lasry, J. Lebuchoux, P. Lions, and N. Touzi, Applications of Malliavin calculus to Monte Carlo methods in finance, Finance and Stochastics, vol.3, issue.4, pp.391-412, 1999.
DOI : 10.1007/s007800050068

J. Sanders and E. Kandrot, CUDA by Example: An Introduction to General-Purpose GPU Programming, 2010.

S. Cook, CUDA Programming: A Developer's Guide to Parallel Computing with GPUs, 2012.

P. L. Ecuyer and R. Simard, TestU01: A C Library for Empirical Testing of, Random Number Generators ACM Transactions on Mathematical Software, vol.33, issue.22, 2007.

O. Bardou, N. Frikha, and G. Pagès, Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling, Monte Carlo Methods and Applications, vol.15, issue.3, pp.173-210, 2009.
DOI : 10.1515/MCMA.2009.011
URL : https://hal.archives-ouvertes.fr/hal-00497588

C. Joy, P. P. Boyle, and K. S. Tan, Quasi-Monte Carlo Methods in Numerical Finance, Management Science, vol.42, issue.6, pp.926-938, 1996.
DOI : 10.1287/mnsc.42.6.926

L. Tierney, Markov Chains for Exploring Posterior Distributions, The Annals of Statistics, vol.22, issue.4, 1994.
DOI : 10.1214/aos/1176325750