Monte Carlo Methods

Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to obtain numerical results. They are particularly useful for estimating complex mathematical functions and simulating the behavior of various systems. Common characteristics include their ability to model uncertainty and their application in diverse fields such as finance, engineering, and physics. These methods are widely used in scenarios where deterministic solutions are difficult or impossible to obtain. For instance, they can be employed to assess risk in financial portfolios or to solve integrals in high-dimensional spaces.