Monte Carlo Simulation

Monte Carlo Simulation is a widely practiced quantitative risk analysis technique. Used from the 1940’s in scientific, business and other applications, MCS addresses key shortcomings of deterministic models. It allows us to answer such critical questions as:

• How likely am to meet the business objectives?
• How risky is each of several outcomes of my decisions?
• Where are the key risks to the successful outcomes of my decisions?
• What actions are appropriate for risk-return levels I am comfortable with?

How did the workshop benefit students?
This one – day program introduced students to spreadsheet – based Monte Carlo simulation. At the end of it, they were able to:

• Understand what uncertainty and risk are and how they affect business decisions.
• Incorporate uncertainty in spreadsheet business models.
• Interpret and present the result of Monte Carlo simulation to improve decision making under uncertainty.

What was covered?
Risk: Key Concepts
Analysis risk: limitation of using point estimates
Working with risk simulation model results

• Frequencies /cumulative frequencies
• Sensitivity analysis

Building a risk simulation model
A quick look at some basic statistics.

• Statistical measures
• Random variables
• Probability density / distribution
• Goodness of fit
• Regression and correlation

Selecting appropriate distribution

• Fitting distributions to observed data
• Deriving distribution from experts

QRS revisited

• Common errors
• Modeling correlation
• Truncating distributions
• Sensitivity