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### Subject 1. Steps in simulation

Simulation is a risk analysis technique in which a computer is used to simulate probable future events and thus to estimate the profitability and risk of a project. It can be used to assess continuous risk.

Steps:

1. Determine "probabilistic" variables. Focus on a few variables that have a significant impact on value.

2. Define probability distributions for these variables.

There are three ways to develop distributions:

• Historical data. This approach is possible for variables that have a long history and reliable data over that history.
• Cross-sectional data.
• Statistical distribution and parameters.

3. Check for correlation across variables. For example, stock prices tend to go up on average. Are two variables (e.g., stock A price and stock B price) correlated? If so, pick only one, or build the correlation into the simulation.

4. Run the simulation. The number of simulations you run is determined by:

• Number of probabilistic inputs.
• Characteristics of probability distributions.
• Range of outcomes.

#### Practice Question 1

In developing a simulation model, you should be concerned if you find that two variables:

I. have a strong, positive correlation.
II. have zero correlation.
III. have a strong, negative correlation.

A. I only
B. I and III
C. I, II and III

A strong correlation can be either a positive or a negative correlation.

#### Practice Question 2

Your company is considering starting a new production division. In the simulation model one probabilistic variable is future sales. The number of simulations will be largest if the future sales amount is assumed to:

A. be normally distributed with a mean of 50k and a standard deviation of 10,000.
B. have a uniform distribution.
C. be based on historical sales distributions of competitors in the industry.