R. Beauwens and A. , Selection of papers presented at the IMACS Seminar on Monte Carlo Methods, Math. Comput. Simulation, vol.47, pp.83-518, 1998.

R. Haddad, C. Lécot, and P. L. Ecuyer, Quasi-Monte Carlo Simulation of Discrete-Time Markov Chains on Multidimensional State Spaces, Monte Carlo and Quasi- Monte Carlo Methods, pp.413-429, 2006.
DOI : 10.1007/978-3-540-74496-2_24

URL : https://hal.archives-ouvertes.fr/hal-00388460

K. Entacher and W. , Editorial, Special Issue: 3rd IMACS Seminar on Monte Carlo Methods, pp.217-571, 2003.
DOI : 10.1016/S0378-4754(02)00219-7

H. Johnson, Options on the Maximum or the Minimum of Several Assets, The Journal of Financial and Quantitative Analysis, vol.22, issue.3, pp.277-283, 1987.
DOI : 10.2307/2330963

C. Lécot, Ein direktes Monte-Carlo-Simulationsverfahren und gleichverteilte Folgen zur L??sung der Boltzmann-Gleichung, Computing, vol.38, issue.1-2, pp.41-57, 1989.
DOI : 10.1007/BF02238728

C. Lécot and B. Tuffin, Quasi-Monte Carlo Methods for Estimating Transient Measures of Discrete Time Markov Chains
DOI : 10.1007/978-3-642-18743-8_20

C. Lécot and B. Tuffin, Comparison of quasi-Monte Carlo-based methods for simulation of Markov chains, Monte Carlo Methods Appl, pp.377-384, 2004.

P. L. Ecuyer, Good Parameters and Implementations for Combined Multiple Recursive Random Number Generators, Operations Research, vol.47, issue.1, pp.159-164, 1999.
DOI : 10.1287/opre.47.1.159

P. L. Ecuyer, C. Lécot, and B. Tuffin, Randomized quasi-Monte Carlo simulation of Markov chains with an ordered state space, Monte Carlo and Quasi-Monte Carlo Methods, pp.331-342, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00388455

P. L. Ecuyer, C. Lécot, and B. Tuffin, A Randomized Quasi-Monte Carlo Simulation Method for Markov Chains, Operations Research, vol.56, issue.4, pp.958-975, 2008.
DOI : 10.1287/opre.1080.0556

URL : https://hal.archives-ouvertes.fr/hal-00388442

H. Niederreiter, Random Number Generation and Quasi-Monte Carlo Methods, 1992.
DOI : 10.1137/1.9781611970081