Difference between revisions of "Monte-Carlo Simulation"

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== Definition ==
 
== Definition ==
'''Monte-Carlo Simulation''' is a common method that is to study stochastic uncertainty.  
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'''Monte-Carlo Simulation''' is a common method that is to study quantifiable stochastic [[Uncertainty]].  
  
 
Using Monte Carlo simulation, various probability distributions for uncertain parameters and/or events can be sampled. The probability distributions of the uncertain data must first be defined, including potential dependencies.  A uniform distribution might be used when uncertainty is described by a range of values.
 
Using Monte Carlo simulation, various probability distributions for uncertain parameters and/or events can be sampled. The probability distributions of the uncertain data must first be defined, including potential dependencies.  A uniform distribution might be used when uncertainty is described by a range of values.
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After specifying the probability distribution a Monte Carlo simulation samples the values from these distributions. Additional calculations might be performed for each [[Scenario]] and/or on the full simulation results.
 
After specifying the probability distribution a Monte Carlo simulation samples the values from these distributions. Additional calculations might be performed for each [[Scenario]] and/or on the full simulation results.
  
[[Category:Quantitative Tools]]
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== Examples ==
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* [[Monte Carlo Simulation of Credit Portfolios]]
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[[Category:Simulation]]

Latest revision as of 13:53, 5 December 2023

Definition

Monte-Carlo Simulation is a common method that is to study quantifiable stochastic Uncertainty.

Using Monte Carlo simulation, various probability distributions for uncertain parameters and/or events can be sampled. The probability distributions of the uncertain data must first be defined, including potential dependencies. A uniform distribution might be used when uncertainty is described by a range of values.

After specifying the probability distribution a Monte Carlo simulation samples the values from these distributions. Additional calculations might be performed for each Scenario and/or on the full simulation results.

Examples