Monte Carlo simulations use random sampling and statistical modeling to estimate mathematical functions and mimic the operations of complex systems. Here’s a simplified process:
1. Define a domain of possible inputs: For example, sales forecasts, market size, and cost estimates. 2. Generate inputs randomly: Use random number generators to produce a wide range of possible input values. 3. Perform a deterministic computation: Apply these inputs to a predefined model (e.g., a financial model). 4. Aggregate the results: Collect and analyze the results from numerous iterations to develop a probability distribution of possible outcomes.