The Monte Carlo simulation is a mathematical technique that predicts possible outcomes of an uncertain event. Computer programs use this method to analyze past data and predict a range of future outcomes based on a choice of action. For example, if you want to estimate the first month’s sales of a new product, you can give the Monte Carlo simulation program your historical sales data. The program will estimate different sales values based on factors such as general market conditions, product price, and advertising budget.
Companies use Monte Carlo methods to assess risks and make accurate long-term predictions. The following are some examples of use cases.
Business
Business leaders use Monte Carlo methods to project realistic scenarios when making decisions. For example, a marketer needs to decide whether it's feasible to increase the advertising budget for an online yoga course. They could use the Monte Carlo mathematical model on uncertain factors or variables such as the following:
- Subscription fee
- Advertising cost
- Sign-up rate
- Retention
The simulation would then predict the impact of changes on these factors to indicate whether the decision is profitable.
Finance
Financial analysts often make long-term forecasts on stock prices and then advise their clients of appropriate strategies. While doing so, they must consider market factors that could cause drastic changes to the investment value. As a result, they use the Monte Carlo simulation to predict probable outcomes to support their strategies.
Online gaming
Strict regulations govern the online gaming and betting industry. Customers expect gaming software to be fair and mimic the characteristics of its physical counterpart. Therefore, game programmers use the Monte Carlo method to simulate results and ensure a fair-play experience.
Engineering
Engineers must ensure the reliability and robustness of every product and system they create before making it available to the public. They use Monte Carlo methods to simulate a product’s probable failure rate based on existing variables. For example, mechanical engineers use the Monte Carlo simulation to estimate the durability of an engine when it operates in various conditions.
