Monte Carlo Simulation
Monte Carlo methods are often used to calculate the value of companies, to evaluate investments in projects at a business unit or corporate level, or to evaluate financial derivatives. The concept reviews the basics of the model and explores how and why it is used in organisations.
Technique Overview
Monte Carlo Simulation Definition
Monte Carlo simulation is essentially “a random number generator useful for forecasting, estimation, and risk analysis. A simulation calculates numerous scenarios of a model by repeatedly picking values from the probability distribution for the uncertain variables and using those values for the event – events such as totals, net profit, or gross expenses” (Mun, 2006:2).
Monte Carlo Simulation Description *
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Business Evidence
Strengths, weaknesses and examples of Monte Carlo Simulation *
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Business Application
Implementation, success factors and measures of Monte Carlo Simulation *
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Professional Tools
Monte Carlo Simulation videos and downloads *
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Further Reading
Monte Carlo Simulation web and print resources *
Monte Carlo Simulation references (4 of up to 20) *
- Berry, R. (2013) An Overview of Value-at-Risk: Part III – Monte Carlo Simulations VaR [Online]. Available at (www.jpmorgan.com/tss/General/Risk_Management/1159380637650).
- CFA Institute (2007) Quantitative Investment Analysis. Wiley, New Jersey.
- Fu, M.C. and Hu, J.-Q. (1995) Sensitivity Analysis for Monte Carlo Simulation of Option Pricing. Probability in the Engineering and Informational Sciences, Vol. 9(3), p. 417-46.
- Hindle, T. (2008) The Economist Guide to Management Ideas and Gurus. The Economist, Profile Books.
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