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Monte Carlo Simulation is an important addition to the EXPO family of products which allows users to perform Monte Carlo simulations on an unlimited number of securities and to display simulated outcomes visually. Monte Carlo Simulation is one of the most powerful mechanisms for advanced risk management and performance evaluation of securities and portfolios. It is increasingly being used by traders and portfolio managers to track the hypothetical performance of a portfolio according to many randomly generated market price paths.
The purpose of Monte Carlo Simulation is to evaluate by experiment quantities that would be very difficult or impossible to evaluate analytically. Such experiments typically begin by creating a set of data with known statistical properties. This is achieved by specifying every aspect of data generating process (DGP), or class of such processes, and replacing the random errors of the DGP by pseudo-random numbers (numbers generated deterministically to mimic a random process with a particular distribution).
An investigator usually generates a large number of such artificial data sets to investigate statistical techniques which analyze these data as if the process generating them were not known. The performance of the statistical technique in revealing some characteristic of the dataset may then be evaluated by generating its distribution from independent replications of the experiment and comparing the results with the known characteristics of the DGP.
Unlike analytical studies, Monte Carlo simulations can not produce exact results. Nonetheless, Monte Carlo results are useful when analytical results are difficult to obtain. In particular, Monte Carlo experiments are often used to investigate the finite sample performance of statistical techniques, the analytical properties of which are known only asymptotically.
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