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.
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.