what is the monte carlo simulation

Monte Carlo simulation is a mathematical technique that uses repeated random sampling to obtain numerical results and predict the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. It is a chance to see into the future and understand the impact of risk and uncertainty. Monte Carlo simulation is used to solve mathematical or statistical problems and evaluate the risk and uncertainty that would affect the outcome of different decision options. It is commonly used to estimate the probability of cost overruns in large projects, the likelihood that an asset price will move in a certain way, and to incorporate the total effects of uncertainty in variables like sales volume, commodity and labor prices, interest and exchange rates, as well as the effect of distinct risk events. Unlike a normal forecasting model, Monte Carlo simulation predicts a set of outcomes based on an estimated range of values versus a set of fixed input values. Monte Carlo simulation works by modeling the probability of different outcomes in a process or a system that cannot easily be predicted due to the intervention of random variables, and it uses something called random number generators to recreate the inherent uncertainty of the input parameters.