Monte Carlo and Quasi-Monte Carlo Methods 2010
Leszek Plaskota, Henryk Woźniakowski
Springer Science & Business Media, Aug 23, 2012 - Mathematics - 732 pages
This book represents the refereed proceedings of the Ninth International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Warsaw (Poland) in August 2010. These biennial conferences are major events for Monte Carlo and the premiere event for quasi-Monte Carlo research. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. The reader will be provided with information on latest developments in these very active areas. The book is an excellent reference for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance and statistics.
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ˇ ˇ ˇ algorithm applied approximation Asian option asymptotic Brownian bridge Brownian motion calculate Carlo and Quasi-Monte Carlo Methods 2010 coefficients Complexity component computational consider constant construction convergence rate d-dimensional defined denote density deterministic diffusion dimension discretisation distribution dual lattice efficiency equation estimate example exponential finite function given Halton sequence importance sampling integrand integration inverse jumps kernel L´evy processes lattice points Lemma linear low discrepancy sequence low-discrepancy sequence lower bound Markov chain Math matrix MCMC Monte Carlo methods multivariate Niederreiter number of points obtain optimal option parameters path payoff permutation photon mapping photons point set polynomial polynomial lattice rules probability problem Proceedings in Mathematics proof Quasi-Monte Carlo Methods randomized algorithm RQMC scheme Sect simulation solution space Springer-Verlag star discrepancy stochastic Theorem tractability trigonometric degree upper bound values variance reduction vector weights Wo´zniakowski eds worst-case error