Spreadsheet risk analysis using simulation

Abstract

For many financial models implemented in electronic spreadsheets, input data values frequently are random variables because they are actually estimates of unknown quantities. As a result, the bottom-line performance measure of the model is a random variable, and risk is associated with decisions based upon it due to the uncertainty in its value. We describe in detail how to evaluate this risk using simulation in a spreadsheet and illustrate the procedure with an example. Formulas for generating random variates from many common distributions using LOTUS 1-2-3 are given, and data analysis considerations are also discussed.

Monte Carlo simulation on microcomputers

“…the normal distribution is available as a function in @Risk, his macros could be simplified. Seila and Banks in the September 1990 issue of SIMULATION [14] demonstrate the use of their own 1-2-3 macros and ten formulas for risk analysis. Further, they suggest ways to analyze the output distributions.…”

Using Software to Solve Engineering Economy Problems

“…Spreadsheets have been under consideration by more authors [4], [14]- [18]. Also, Seila and Banks [19] showed how to use Lotus123 in order to solve a problem in engineering economy by simulation. Coates and Kuhl [20] illustrated the use of simulation software for solving engineering economy problems by three examples.…”

Stochastic income statement planning as a basis for risk assessment in the context of emissions trading

“…Coats and Chesser, 1982;Seila and Banks, 1990;L'Ecuyer, 2009). With this method, the probability distribution of a decision variable is determined rather than a single value.…”