What is Monte Carlo simulation used for in quantitative business analysis?

What is Monte Carlo simulation used for in quantitative business analysis?

• A. To test for normality.
• B. To measure seasonality only.
• C. To model uncertainty by random sampling, estimate distributions of outputs, and perform risk analysis.
• D. To compute bootstrapped standard errors.

Answer: (C)

Monte Carlo simulation focuses on quantifying uncertainty by drawing random samples from defined probability distributions for uncertain inputs and propagating those samples through a model to produce a distribution of possible outputs. By repeating many trials, you build up the distribution of outcomes (such as cash flows, profit, or NPV) and can assess risk with metrics like the probability of different results, expected value, and the spread of outcomes. This approach lets you analyze how input variability affects results and supports decision-making under uncertainty, including exploring different scenarios and their likelihoods. It's not about testing whether data are normally distributed, nor is it limited to measuring seasonality patterns, and it's a different technique from bootstrapping standard errors.

Monte Carlo simulation focuses on quantifying uncertainty by drawing random samples from defined probability distributions for uncertain inputs and propagating those samples through a model to produce a distribution of possible outputs. By repeating many trials, you build up the distribution of outcomes (such as cash flows, profit, or NPV) and can assess risk with metrics like the probability of different results, expected value, and the spread of outcomes. This approach lets you analyze how input variability affects results and supports decision-making under uncertainty, including exploring different scenarios and their likelihoods. It's not about testing whether data are normally distributed, nor is it limited to measuring seasonality patterns, and it's a different technique from bootstrapping standard errors.