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For example, a comparison of a spreadsheet cost construction model run using traditional "what if" scenarios, and then running the comparison again with Monte Carlo simulation and triangular probability distributions shows that the Monte Carlo analysis has a narrower range than the "what if" analysis.
The simulation data is used to define the scenario index for each simulation run. For example, if an X2 value falls into the low state and X3 is equal to 2, the corresponding scenario, defined in Step 3, is (ii). Color-code the output distribution. When all output values are assigned scenario indices, they are plotted as series in a stacked ...
The Monte Carlo method in Excel Prof. André Farber Solvay Business School; Sales Forecasting, vertex42.com; Pricing using Monte Carlo simulation, a practical example, Prof. Giancarlo Vercellino; Personal finance. A Better Way to Size Up Your Nest Egg, Businessweek Online: January 22, 2001
Monte Carlo is an estimation procedure. The main idea is that if it is necessary to know the average value of some random variable and its distribution cannot be stated, and if it is possible to take samples from the distribution, we can estimate it by taking the samples, independently, and averaging them.
Libraries of such procedures are included with the program and can be merged into files as needed. A list solver feature allows variables to be associated with ranges of data or probability distributions, solving for multiple values, which is useful for generating tables and plots and for running Monte Carlo simulations.
The proportion of simulation trials surpassing the default point represents the default probability for a given year. The simulation is typically created in an Excel worksheet. Each row of the worksheet represents a different user specified series. Series may contain random numbers, macroeconomic variables, revenues, expenditures and debt levels.
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