Traditional sensitivity analysis involves testing a limited number of scenarios (e.g., base, upside, and downside). Each scenario is a set of predefined inputs.
This approach shows the outcomes of the model from various perspectives but does not give a precise likelihood of a particular result to happen. In contrast, the Monte Carlo method tests a large number (several hundreds or thousands) of ‘scenarios’ in which the inputs are drawn as random numbers. The results of the model (gross profit, IRR, etc.) are also represented by ranges of numbers.
By analyzing statistical patterns of those ranges, the analyst can determine mathematically the chances of output being within a specific range or being higher or lower than a certain threshold. In this publication, I am sharing a technique of Monte Carlo analysis in Excel.
My approach is based on standard Excel functions and data tables without macros. The accompanying model performs essential Monte Carlo simulation: drawing random numbers of certain distribution types, making correlations, and interpreting the outcomes.
You will get two downloadable files: 1 Full Excel Template and 1 PDF file with Instructions and Explanations.
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