Difference between revisions of "Monte-Carlo Simulation"
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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. | ||
+ | |||
+ | == Examples == | ||
+ | * [[Monte Carlo Simulation of Credit Portfolios]] | ||
[[Category:Quantitative Tools]] | [[Category:Quantitative Tools]] |
Revision as of 20:42, 21 November 2022
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.