Monte Carlo simulation

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Monte Carlo simulation

An analytical technique for solving a problem by performing a large number of trail runs, called simulations, and inferring a solution from the collective results of the trial runs. Method for calculating the probability distribution of possible outcomes.

Monte Carlo Simulation

A computer simulation that seeks to determine the likelihood of various scenarios by running multiple simulations using random variables. The results of the Monte Carlo simulation show the most likely outcomes.

Monte Carlo simulation.

A Monte Carlo simulation can be used to analyze the return that an investment portfolio is capable of producing. It generates thousands of probable investment performance outcomes, called scenarios, that might occur in the future.

The simulation incorporates economic data such as a range of potential interest rates, inflation rates, tax rates, and so on. The data is combined in random order to account for the uncertainty and performance variation that's always present in financial markets.

Financial analysts may employ Monte Carlo simulations to project the probability of your retirement account investments producing the return you need to meet your long-term goals.

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The Monte Carlo technique has since been developed by scientists for use in radiotherapy treatments for cancer patients.
He also holds a MS degree from the University of Western Ontario in medical physics, where he applied Monte Carlo techniques to high- dose-rate brachytherapy and fluoroscopic imaging at the London Regional Cancer Centre, London, Ontario, Canada.
Methods for improved calculation of these effects are under development by Monte Carlo techniques or direct solution of the drift kinetic equation.
Among specific topics are the decomposition of the optical polarization components of the Crab pulsar and its nebula, the analysis of single pulses from radio pulsars at high observing frequencies, the population synthesis of normal radio and gamma-ray pulsars using Markov chain Monte Carlo techniques, symmetry energy effects in the neutron star properties, and radio timing observations of four gamma-ray pulsars at Nanshan.
Continuing to focus on analytic strategies for regression problems for practical situations in which predictors are measured with error, this edition includes developments across the last decade, including greatly expanded discussion and applications of Bayesian computation through chain Monte Carlo techniques, a new chapter on longitudinal data and mixed models, and new material on nonparametric regression, density estimation, survival analysis, and score functions, with unique data sets available online.
He has published more than 100 archival papers concerned with developments of EPMA instrumentation, improvements in microanalysis techniques, metallurgical and geological applications (including lunar samples and asbestos), characterization of microanalysis standards, uncertainties in quantitative EPMA and correction procedures, bibliographies of EPMA publications, tables of mass absorption coefficients and x-ray lines, development of matrix correction procedures, the early use of color in wavelength dispersive x-ray dot mapping, energy dispe rsive qualitative and quantitative analysis, and the use of Monte Carlo techniques in quantitative EPMA.
new implant model using Monte Carlo techniques for SiC in TMA's
Case studies illustrate the use of GMRFs in complex hierarchical models in which statistical inference is only possible using Markov chain Monte Carlo techniques.
Initial chapters provide a short treatment of the probability and statistics needed as background, enabling those without experience in Monte Carlo techniques to apply these ideas to their research.
The organization's solutions enable financial institutions to comply with Basel II and IAS39, simulate interest rate risk on the banking book and fully test hedge effectiveness using Monte Carlo techniques.
The organization's enterprise risk management solutions enable financial institutions to comply with the pillars of Basel II, simulate interest rate risk on the banking book and fully test hedge effectiveness, using Monte Carlo techniques, for IAS 39 compliance.
E[acute accent]In addition to the chapter on Monte Carlo techniques, the Yearbook tracks the performance of six U.