Advanced Monte Carlo Methods and Applications
نویسندگان
چکیده
منابع مشابه
Monte Carlo and quasi-Monte Carlo methods
Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~^), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Ca...
متن کاملInstitute for Advanced Simulation Monte Carlo and Kinetic Monte Carlo Methods – A Tutorial
c © 2009 by John von Neumann Institute for Computing Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher ment...
متن کاملAdvanced Monte Carlo methods for barrier and related exotic options
In this work, we present advanced Monte Carlo techniques applied to the pricing of barrier options and other related exotic contracts. It covers in particular the Brownian bridge approaches, the barrier shifting techniques (BAST) and their extensions as well. We leverage the link between discrete and continuous monitoring to design efficient schemes, which can be applied to the Black-Scholes mo...
متن کاملMonte Carlo methods and applications for the nuclear shell model
The shell-model Monte Carlo (SMMC) technique transforms the traditional nuclear shell-model problem into a path-integral over auxiliary fields. We describe below the method and its applications to four physics issues: calculations of sd-pf shell nuclei, a discussion of electron-capture rates in pf -shell nuclei, exploration of pairing correlations in unstable nuclei, and level densities in rare...
متن کاملMonte Carlo sampling methods using Markov chains and their applications
A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to numerical problems arising ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
سال: 2017
ISSN: 2376-7642,2376-7642
DOI: 10.1061/ajrua6.0000921