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