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  2. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    Monte Carlo method: Pouring out a box of coins on a table, and then computing the ratio of coins that land heads versus tails is a Monte Carlo method of determining the behavior of repeated coin tosses, but it is not a simulation. Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one ...

  3. Monte Carlo methods in finance - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_in_finance

    In finance, the Monte Carlo method is used to simulate the various sources of uncertainty that affect the value of the instrument, portfolio or investment in question, and to then calculate a representative value given these possible values of the underlying inputs. [1] (". Covering all conceivable real world contingencies in proportion to ...

  4. Monte Carlo methods for option pricing - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_methods_for...

    Monte Carlo methods for option pricing. In mathematical finance, a Monte Carlo option model uses Monte Carlo methods [Notes 1] to calculate the value of an option with multiple sources of uncertainty or with complicated features. [1] The first application to option pricing was by Phelim Boyle in 1977 (for European options ).

  5. Kinetic Monte Carlo - Wikipedia

    en.wikipedia.org/wiki/Kinetic_Monte_Carlo

    The kinetic Monte Carlo (KMC) method is a Monte Carlo method computer simulation intended to simulate the time evolution of some processes occurring in nature. Typically these are processes that occur with known transition rates among states. It is important to understand that these rates are inputs to the KMC algorithm, the method itself ...

  6. Variance reduction - Wikipedia

    en.wikipedia.org/wiki/Variance_reduction

    In mathematics, more specifically in the theory of Monte Carlo methods, variance reduction is a procedure used to increase the precision of the estimates obtained for a given simulation or computational effort. [1] Every output random variable from the simulation is associated with a variance which limits the precision of the simulation results ...

  7. Stochastic simulation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_simulation

    Stochastic simulation. A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. [1] Realizations of these random variables are generated and inserted into a model of the system. Outputs of the model are recorded, and then the process is repeated with a new ...

  8. Credit valuation adjustment - Wikipedia

    en.wikipedia.org/wiki/Credit_valuation_adjustment

    The full calculation of CVA, as above, is via a Monte-Carlo simulation on all risk factors; this is computationally demanding. There exists a simple approximation for CVA. This consists in buying default protection, typically a Credit Default Swap, netted for each counterparty.

  9. Quantum Monte Carlo - Wikipedia

    en.wikipedia.org/wiki/Quantum_Monte_Carlo

    Quantum Monte Carlo encompasses a large family of computational methods whose common aim is the study of complex quantum systems. One of the major goals of these approaches is to provide a reliable solution (or an accurate approximation) of the quantum many-body problem. The diverse flavors of quantum Monte Carlo approaches all share the common ...

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