Valuation analysis often relies on imprecise inputs. To compensate for this uncertainty, valuation analysts sometimes employ a range of inputs to represent likely “what-if” scenarios, such as sets of “low,” “high,” and “expected” input values. While this rough approximation may be acceptable for the purposes of many analyses, the results tend to reflect bias and estimation error on the part of the valuation analyst as the input selection essentially distills a large number of possible inputs down to a handful. Monte Carlo simulation method was introduced to valuation analysis to mitigate this kind of error. The Monte Carlo method uses a computer to generate a large number of scenarios based on probabilities for inputs, and gives the valuation analyst insight into the most likely result and the likelihood of other outcomes. Join valuation expert John Elmore for an introduction to the Monte Carlo method for valuing business interests and intangible assets. Get comfortable with Monte Carlo with a straightforward step-by-step guide for applying the Monte Carlo method using familiar Excel functions without the need for employing more complicated simulation software or Excel plugins. 

Overview of the Monte Carlo Simulation Method

• Monte Carlo simulation defined
• Steps involved in a Monte Carlo simulation
• Overview of relevant Excel functions used to generate a Monte Carlo simulation

Measuring Uncertainty

• Identifying uncertainty in valuation analysis
• Understanding how to model the uncertainty as a distribution of possible inputs

Applying the Monte Carlo Method with Step-by-Step Examples

• Valuation of an ownership interest in a company
• Valuation of an intangible asset

Monte Carlo Method Resources for Reference and Further Study