Monte Carlo method

Computation intensive forecasting technique applied where statistical analysis is extremely cumbersome due to the complexity of a problem (such as queuing or waiting line probabilities, or inventories involving millions of items). Used only where the problem has a chance (random) component, and is subject to unpredictable influences, it simulates (models) a situation on the basis of current and past (historical) data. In the simulation process, it computes an equation (mathematical model) thousands or millions of times, each time injecting random numbers to come up with a range of possibilities or outcomes of possible actions. Larger the number of computations, the greater the probability (according to the law of large numbers) of approximating the future events-provided the maximum-amount of known-data is incorporated into the model. Named after the Mediterranean resort of Monte Carlo in Monaco (famous for its gambling casinos) where sophisticated betters employ scientific methods to enhance their chances to win.