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

Let's see one

In Excel

What About Perl?