Examples of Stochastic Simulations: Monte Carlo Simulations

Walter R. Paczkowski
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Walter R. Paczkowski: Data Analytics Corp.

Chapter Chapter 10 in Predictive and Simulation Analytics, 2023, pp 263-292 from Springer

Abstract: Abstract I introduced random numbers in Chap. 9 as the backbone for stochastic simulations. Simulations are one part of a two-part process for analyzing and predicting consequences, what I called these implications and ramifications (I&R), of business decisions. These are usually broader in scope than typically assumed. The reason for this broad scope is the complex system nature of a business. Because of this complexity, an impact on one part of the system affects all the other parts. The only way to understand the I&R for the entire system is via simulations. One very important example of a simulation is the Monte Carlo simulation, which is my subject for this chapter.

Date: 2023
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DOI: 10.1007/978-3-031-31887-0_10

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