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Monte Carlo method: Pouring out a box of coins on a table, and then computing the ratio of coins that land heads versus tails is a Monte Carlo method of determining the behavior of repeated coin tosses, but it is not a simulation. Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one ...
The variance of randomly generated points within a unit square can be reduced through a stratification process. In mathematics, more specifically in the theory of Monte Carlo methods, variance reduction is a procedure used to increase the precision of the estimates obtained for a given simulation or computational effort. [1]
Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. In statistical mechanics applications prior to the introduction of the Metropolis algorithm, the method consisted of generating a large number of random configurations of the system, computing the properties of interest (such as energy or density) for each configuration ...
The kinetic Monte Carlo (KMC) method is a Monte Carlo method computer simulation intended to simulate the time evolution of some processes occurring in nature. Typically these are processes that occur with known transition rates among states.
Monte Carlo simulated stock price time series and random number generator (allows for choice of distribution), Steven Whitney; Discussion papers and documents. Monte Carlo Simulation, Prof. Don M. Chance, Louisiana State University; Pricing complex options using a simple Monte Carlo Simulation, Peter Fink (reprint at quantnotes.com)
GNU MCSim is a suite of simulation software. It allows one to design one's own statistical or simulation models, perform Monte Carlo simulations, and Bayesian inference through (tempered) Markov chain Monte Carlo simulations. The latest version allows parallel computing of Monte Carlo or MCMC simulations.
Another important concept related to the Monte Carlo integration is the importance sampling, a technique that improves the computational time of the simulation. In the following sections, the general implementation of the Monte Carlo integration for solving this kind of problems is discussed.
Monte Carlo methods are used in corporate finance and mathematical finance to value and analyze (complex) instruments, portfolios and investments by simulating the various sources of uncertainty affecting their value, and then determining the distribution of their value over the range of resultant outcomes.