Abstract
We incorporate potential effects of uncertainty in our analysis to account for the fact that we don’t know what will happen in the future. Monte Carlo simulation is the method that allows us to include these considerations of uncertainty analytically.
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Notes
- 1.
The interval might actually be as large as the domain itself, as is the case with a normal distribution, which spans all real numbers even though the bulk of the distribution can be assigned to exist within a relatively narrow range of dispersion.
- 2.
Peter McNamee and John Celona, Decision Analysis with Supertree (2nd ed., San Francisco: The Scientific Press, 1990).
- 3.
R. E. Megill, An Introduction to Risk Analysis (2nd ed., Tulsa, OK: PennWell, 1984).
- 4.
There are several other methods that have been proposed for simulating distributions with discrete weightings for three distinct values. All of them essentially use the same approach described here.
- 5.
Gregory S. Parnell PhD, Terry Bresnick MBA, Steven N. Tani PhD, Eric R. Johnson PhD, Handbook of Decision Analysis (Hoboken, NJ: Wiley, 2013, pp. 256-257).
- 6.
Describing a probability with a distribution naturally leads to the question of why we wouldn’t then describe each probability within that distribution with another distribution, ultimately leading to an infinite regress. Instead, we think about probabilities as degrees of belief that well-defined events will occur or not. The actual probability assigned to a specific event results from a ratio of bets one would place for and against the event happening. Because one would only have a fixed purse of money to bet, the final allocation of bets are single points, not uncertain ranges. In short, probabilities are, themselves, statements of uncertainty. We don’t need to compound uncertainty further by layering on more uncertainty. Oops, I said I wouldn’t get into this discussion here.
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© 2018 Robert D. Brown III
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Brown III, R.D. (2018). Include Uncertainty in the Financial Analysis. In: Business Case Analysis with R. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3495-2_3
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DOI: https://doi.org/10.1007/978-1-4842-3495-2_3
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