What Is a Monte Carlo Simulation?

Monte Carlo Simulation Definition

The Monte Carlo Simulation, also referred to as a multiple probability simulation, is a probability model used to predict the probability of various outcomes actually occurring.

Defining Monte Carlo Simulation in Simple Terms

The financial field is constantly attempting to predict outcomes.

Whether it be the performance of a stock, or the viability of an individual paying back their loan, members of the financial community are always wondering what’s going to happen next.

Unfortunately, even the best predictions are not impenetrable to the effect of random variables.

Which as a result increases the possibility of both risk and uncertainty for any financier.

The Monte Carlo Simulation then, is used to help mitigate the possibility of unpredicted outcomes.

How the Monte Carlo Simulation Works

The way the Monte Carlo Simulation works is by substituting any factor that has inherent uncertainty for a range of values, like probability distribution.

So then, rather than calculating one result the Monte Carlo Simulation can calculate hundreds even thousands of results as well as the likelihood of their occurrence depending on where they fall in the curve of the distribution.

Predicting With the Monte Carlo Simulation

In finance, Monte Carlo Simulations can be used to predict the price movement of a particular stock.

By taking into account the historical data of the stock’s drift and volatility, then inputting those points of data into the simulation; an analyst is then able to determine the likelihood of the stock moving one way or another in the future.

Beyond Finance

However, the Monte Carlo simulation is not limited to merely the field of finance as it is also used to predict outcomes in physics, engineering, agriculture and in gambling which is what the simulation was originally created to aid.

Monte Carlo Simulation FAQs

The Monte Carlo Simulation, also referred to as a multiple probability simulation, is a model used to predict the chances of various outcomes actually occurring.
The way the Monte Carlo Simulation works is by substituting any factor that has inherent uncertainty for a range of values, like probability distribution.
In finance, Monte Carlo Simulations can be used to predict the price movement of a particular stock.
Even the best predictions such as the Monte Carlo are not immune to the effect of random variables, which increase the possibility of risk and uncertainty for any financier. The Monte Carlo Simulation then, is used to help mitigate the possibility of unpredicted outcomes.
The Monte Carlo Simulation is also used to predict outcomes in physics, engineering, agriculture, and gambling. The latter is what the simulation was originally created for.
True Tamplin, BSc, CEPF®

About the Author
True Tamplin, BSc, CEPF®

True Tamplin is a published author, public speaker, CEO of UpDigital, and founder of Finance Strategists.

True contributes to his own finance dictionary, Finance Strategists, and has spoken to various financial communities such as the CFA Institute, as well as university students like his Alma mater, Biola University, where he received a bachelor of science in business and data analytics.

To learn more about True, visit his personal website, view his author profile on Amazon, his interview on CBS, or check out his speaker profile on the CFA Institute website.