Monte Carlo Analysis (without macros) Excel Model
![Monte Carlo Analysis (without macros) Excel Model - Templarket - Business Templates Marketplace]()
![Monte Carlo Analysis (without macros) Excel Model - Templarket - Business Templates Marketplace]()
![Monte Carlo Analysis (without macros) Excel Model - Templarket - Business Templates Marketplace]()
A 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 at 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 distributions of those numbers follow the statistical patterns determined by the analyst (ranges, distribution types, target mean, median, mode, correlations between the inputs).
The results of the model (gross profit, ,margins, IRR etc.) are also represented by ranges of numbers. Analyzing statistical patterns of those ranges the analyst can determine mathematically the chances of an 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 file performs essential Monte Carlo simulation and covers drawing random numbers under certain distribution types and characteristics, making correlations and interpreting the outcomes. The file includes statistical charts (histograms, scatter plot) to illustrate the results.
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 distributions of those numbers follow the statistical patterns determined by the analyst (ranges, distribution types, target mean, median, mode, correlations between the inputs).
The results of the model (gross profit, ,margins, IRR etc.) are also represented by ranges of numbers. Analyzing statistical patterns of those ranges the analyst can determine mathematically the chances of an 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 file performs essential Monte Carlo simulation and covers drawing random numbers under certain distribution types and characteristics, making correlations and interpreting the outcomes. The file includes statistical charts (histograms, scatter plot) to illustrate the results.
