A Monte Carlo simulation is a process used to show all the potential outcomes of a trading system, business model, supply chain, scientific theory, insurance, research and development, or a casino. A Monte Carlo simulation uses the most important available metrics of a system including inputs of size of wins and losses along with win rates and other probabilities to compute all the future possibilities of a system or process. 

A Monte Carlo simulation does multiple risk and reward calculations by creating potential models of multiple outcomes by processing a wide range of values to create a graphic of probability distribution. It attempts to remove some of the uncertainty of implementing a system by showing the range of potential outcomes based on the factors of the system. It can calculate new results after the parameters of a system are adjusted to look for better potential outcomes. A Monte Carlo simulation can show thousands of potential outcomes based on the input of variables in a system. 

The purpose of a Monte Carlo simulation is to create and show the variance of distribution of possible outcome results based on the parameters of a system. It is used for risk management and optimization of rewards for a system with measurable inputs. It seeks to create some clarity around future results.   

monte carlo simulation

By Steve Burns

After a lifelong fascination with financial markets, Steve began investing in 1993 and trading his accounts in 1995. It was love at first trade. After more than 30 successful years in the markets, Steve now dedicates his time to helping traders improve their psychology and profitability. New Trader U offers an extensive blog resource with more than 4,000 original articles, online courses, and best-selling books covering various topics.