## Monte Carlo Simulation

### Part One

Peter Bowen

## What is a Monte Carlo Simulation?

Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.

## When is it Useful?

- Complex and Difficult Problem
- Many Independant Variables
- Counter Intuitive
- Large Variation in result
- Directionality is Important

## It is not

- What if Scenario
- Bounds Based Analysis
- Sensitivity Analysis

## What it is...

- Defined domain of possible inputs
- Generate random input values using an appropriate distribution
- Deterministic computation related to the inputs
- Aggrigatioon and analysis of the results