Uses of Interface
net.finmath.montecarlo.IndependentIncrements
Packages that use 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
Constructors in net.finmath.modelling.modelfactory with parameters of type IndependentIncrementsModifierConstructorDescriptionAssetModelMonteCarloFactory(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)
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Uses of IndependentIncrements in net.finmath.montecarlo
Subinterfaces of IndependentIncrements in net.finmath.montecarloModifier and TypeInterfaceDescriptioninterface
Interface description of a time-discrete n-dimensional Brownian motion W = (W1,...,Wn) where Wi is a Brownian motion.Classes in net.finmath.montecarlo that implement IndependentIncrementsModifier 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.Methods in net.finmath.montecarlo that return IndependentIncrementsModifier 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)
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Uses of IndependentIncrements in net.finmath.montecarlo.assetderivativevaluation
Constructors in net.finmath.montecarlo.assetderivativevaluation with parameters of type IndependentIncrementsModifierConstructorDescriptionMonteCarloAssetModel(ProcessModel model, IndependentIncrements stochasticDriver)
Convenient constructor being the same as this(new EulerSchemeFromProcessModel(model, stochasticDriver)) -
Uses of IndependentIncrements in net.finmath.montecarlo.process
Methods in net.finmath.montecarlo.process that return IndependentIncrementsModifier and TypeMethodDescriptionEulerSchemeFromProcessModel.getStochasticDriver()
MonteCarloProcess.getStochasticDriver()
Constructors in net.finmath.montecarlo.process with parameters of type IndependentIncrementsModifierConstructorDescriptionEulerSchemeFromProcessModel(ProcessModel model, IndependentIncrements stochasticDriver)
Create an Euler discretization scheme.EulerSchemeFromProcessModel(ProcessModel model, IndependentIncrements stochasticDriver, EulerSchemeFromProcessModel.Scheme scheme)
Create an Euler discretization scheme.