Monte Carlo Simulation is a computational technique used to model and analyze
complex systems or processes by generating random samples of input variables and observing
their impact on the system's output. It is named after the Monte Carlo casino in Monaco, known
for its games of chance. Monte Carlo Simulation is particularly useful in situations where
analytical or closed-form solutions are not feasible, or when the system is influenced by
multiple uncertain factors. It is applied in various fields, including finance, engineering, physics,
economics, and risk analysis. Some specific applications include portfolio optimization, option
pricing, project management, reliability analysis, and decision-making under uncertainty.