Uses of Interface
net.finmath.montecarlo.IndependentIncrements
Package
Description
Provides classes to build models from descriptors.
Provides basic interfaces and classes used in Monte-Carlo models (like LIBOR market model or Monte-Carlo simulation
of a Black-Scholes model), e.g., the Monte-Carlo random variable and the Brownian motion.
Monte-Carlo models for asset value processes, like the Black Scholes model.
Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.
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Uses of IndependentIncrements in net.finmath.modelling.modelfactory
ModifierConstructorDescriptionAssetModelMonteCarloFactory
(IndependentIncrements stochasticDriver) Create the factory.AssetModelMonteCarloFactory
(RandomVariableFactory randomVariableFactory, IndependentIncrements stochasticDriver) Create the factory.AssetModelMonteCarloFactory
(RandomVariableFactory randomVariableFactory, IndependentIncrements stochasticDriver, HestonModel.Scheme scheme) Create the factory.BlackScholesModelMonteCarloFactory
(RandomVariableFactory randomVariableFactory, IndependentIncrements brownianMotion) HestonModelMonteCarloFactory
(HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory, IndependentIncrements brownianMotion) -
Uses of IndependentIncrements in net.finmath.montecarlo
Modifier and TypeInterfaceDescriptioninterface
Interface description of a time-discrete n-dimensional Brownian motion W = (W1,...,Wn) where Wi is a Brownian motion.Modifier and TypeClassDescriptionclass
This class implements a Brownian bridge, i.e., samples of realizations of a Brownian motion conditional to a given start and end value.class
Implementation of a time-discrete n-dimensional Brownian motion W = (W1,...,Wn) where Wi is a Brownian motion and Wi, Wj are independent for i not equal j.class
Implementation of a time-discrete n-dimensional Brownian motion W = (W1,...,Wn) where Wi is a Brownian motion and Wi, Wj are independent for i not equal j.class
Deprecated.Refactor rename.class
A Brownian motion which is defined by some factors of a given Brownian motion, i.e., for a given multi-factorial Brownian motion W, this Brownian motion is given by ( W(i[0]), W(i[1]) W(i[2]), ..., W(i[n-1]) ) where i is a given array of integers.class
Provides a Brownian motion from given (independent) increments and performs a control of the expectation and the standard deviation.class
Provides a correlated Brownian motion from given (independent) increments and a given matrix of factor loadings.class
Implementation of a time-discrete n-dimensional Gamma process \( \Gamma = (\Gamma_{1},\ldots,\Gamma_{n}) \), where \( \Gamma_{i} \) is a Gamma process and \( \Gamma_{i} \), \( \Gamma_{j} \) are independent for i not equal j.class
Implementation of a time-discrete n-dimensional sequence of independent increments W = (W1,...,Wn) form a given set of inverse cumulative distribution functions.class
Implementation of a time-discrete n-dimensional jump process J = (J1,...,Jn) where Ji is a Poisson jump process and Ji, Jj are independent for i not equal j.class
Implementation of the compound Poisson process for the Merton jump diffusion model.class
Implementation of a time-discrete n-dimensional Variance Gamma process via Brownian subordination through a Gamma Process.Modifier and TypeMethodDescriptionGammaProcess.getCloneWithModifiedSeed
(int seed) IndependentIncrements.getCloneWithModifiedSeed
(int seed) Return a new object implementing BrownianMotion having the same specifications as this object but a different seed for the random number generator.IndependentIncrementsFromICDF.getCloneWithModifiedSeed
(int seed) MertonJumpProcess.getCloneWithModifiedSeed
(int seed) VarianceGammaProcess.getCloneWithModifiedSeed
(int seed) GammaProcess.getCloneWithModifiedTimeDiscretization
(TimeDiscretization newTimeDiscretization) IndependentIncrements.getCloneWithModifiedTimeDiscretization
(TimeDiscretization newTimeDiscretization) Return a new object implementing BrownianMotion having the same specifications as this object but a different time discretization.IndependentIncrementsFromICDF.getCloneWithModifiedTimeDiscretization
(TimeDiscretization newTimeDiscretization) MertonJumpProcess.getCloneWithModifiedTimeDiscretization
(TimeDiscretization newTimeDiscretization) VarianceGammaProcess.getCloneWithModifiedTimeDiscretization
(TimeDiscretization newTimeDiscretization) -
Uses of IndependentIncrements in net.finmath.montecarlo.assetderivativevaluation
ModifierConstructorDescriptionMonteCarloAssetModel
(ProcessModel model, IndependentIncrements stochasticDriver) Convenient constructor being the same as this(new EulerSchemeFromProcessModel(model, stochasticDriver)) -
Uses of IndependentIncrements in net.finmath.montecarlo.process
Modifier and TypeMethodDescriptionEulerSchemeFromProcessModel.getStochasticDriver()
MonteCarloProcess.getStochasticDriver()
ModifierConstructorDescriptionEulerSchemeFromProcessModel
(ProcessModel model, IndependentIncrements stochasticDriver) Create an Euler discretization scheme.EulerSchemeFromProcessModel
(ProcessModel model, IndependentIncrements stochasticDriver, EulerSchemeFromProcessModel.Scheme scheme) Create an Euler discretization scheme.