Monte-Carlo Simulation

Definition

Monte-Carlo Simulation is a common method that is to study quantifiable stochastic Uncertainty.

Using Monte Carlo simulation, various probability distributions for uncertain parameters and/or events can be sampled. The probability distributions of the uncertain data must first be defined, including potential dependencies. A uniform distribution might be used when uncertainty is described by a range of values.

After specifying the probability distribution a Monte Carlo simulation samples the values from these distributions. Additional calculations might be performed for each Scenario and/or on the full simulation results.

Examples

• Monte Carlo Simulation of Credit Portfolios