Authors
Hilary L. Emmett & Lawrence I. Goldman
Abstract
The primary focus of Monte Carlo simulation is to identify and quantify risk related to uncertainty and variability in spreadsheet model inputs.
The stress of Monte Carlo simulation often revels logical errors in the underlying spreadsheet that might be overlooked during day-to-day use or traditional "what if" testing. This secondary benefit of simulation requires a trained eye to recognize warning signs of poor model construction.
Sample
Results of the sensitivity chart should always be scrutinized to ensure that the results are consistent with the theoretical positive/negative relationship between the input assumption and the output forecast.
In this example, the OPEX/Sales% appears to have the greatest effect on NPV, but experience suggests that Year 1 sales should have a much higher relative impact on the results of the simulation.
Publication
2004, EuSpRIG
Full article
Identification of logical errors through Monte Carlo simulation
