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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 ...
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)
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.
The Metropolis-Hastings algorithm sampling a normal one-dimensional posterior probability distribution.. In statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult.
The Monte Carlo method for electron transport is a semiclassical Monte Carlo (MC) approach of modeling semiconductor transport. Assuming the carrier motion consists of free flights interrupted by scattering mechanisms, a computer is utilized to simulate the trajectories of particles as they move across the device under the influence of an electric field using classical mechanics.
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.
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