MONTE CARLO ANALYSIS/SIMULATION

Abstract: Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The Underlying concept is to use randomness to solve problems that might be deterministic in principle. A Monte Carlo simulation can be used to tackle a range of problems in virtually every field such as finance, engineering, supply chain, and science. It is also referred to as a multiple probability simulation.

Keywords: random, probability, simulation, statistics, distribution.