Uses of Interface
net.finmath.montecarlo.IndependentIncrements

Packages that use IndependentIncrements

Package	Description
net.finmath.modelling.modelfactory	Provides classes to build models from descriptors.
net.finmath.montecarlo	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.
net.finmath.montecarlo.process	Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.

Uses of IndependentIncrements in net.finmath.modelling.modelfactory

Constructors in net.finmath.modelling.modelfactory with parameters of type IndependentIncrements

Constructor and Description
AssetModelMonteCarloFactory(AbstractRandomVariableFactory randomVariableFactory, IndependentIncrements stochasticDriver, HestonModel.Scheme scheme) Create the factory.
BlackScholesModelMonteCarloFactory(AbstractRandomVariableFactory randomVariableFactory, IndependentIncrements brownianMotion)
HestonModelMonteCarloFactory(HestonModel.Scheme scheme, AbstractRandomVariableFactory randomVariableFactory, IndependentIncrements brownianMotion)

Uses of IndependentIncrements in net.finmath.montecarlo

Subinterfaces of IndependentIncrements in net.finmath.montecarlo

Modifier and Type	Interface and Description
interface	BrownianMotion Interface description of a time-discrete n-dimensional Brownian motion W = (W1,...

Classes in net.finmath.montecarlo that implement IndependentIncrements

Modifier and Type	Class and Description
class	BrownianBridge This class implements a Brownian bridge, i.e., samples of realizations of a Brownian motion conditional to a given start and end value.
class	BrownianMotionLazyInit Implementation of a time-discrete n-dimensional Brownian motion W = (W1,...
class	BrownianMotionView 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	CorrelatedBrownianMotion Provides a correlated Brownian motion from given (independent) increments and a given matrix of factor loadings.
class	GammaProcess 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	IndependentIncrementsFromICDF Implementation of a time-discrete n-dimensional sequence of independent increments W = (W1,...
class	JumpProcessIncrements Implementation of a time-discrete n-dimensional jump process J = (J1,...
class	VarianceGammaProcess Implementation of a time-discrete n-dimensional Variance Gamma process via Brownian subordination through a Gamma Process.

Methods in net.finmath.montecarlo that return IndependentIncrements

Modifier and Type	Method and Description
IndependentIncrements	VarianceGammaProcess.getCloneWithModifiedSeed(int seed)
IndependentIncrements	IndependentIncrementsFromICDF.getCloneWithModifiedSeed(int seed)
IndependentIncrements	GammaProcess.getCloneWithModifiedSeed(int seed)
IndependentIncrements	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.
IndependentIncrements	VarianceGammaProcess.getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization)
IndependentIncrements	IndependentIncrementsFromICDF.getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization)
IndependentIncrements	GammaProcess.getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization)
IndependentIncrements	IndependentIncrements.getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization) Return a new object implementing BrownianMotion having the same specifications as this object but a different time discretization.

Uses of IndependentIncrements in net.finmath.montecarlo.process

Methods in net.finmath.montecarlo.process that return IndependentIncrements

Modifier and Type	Method and Description
IndependentIncrements	EulerSchemeFromProcessModel.getStochasticDriver()
IndependentIncrements	MonteCarloProcess.getStochasticDriver()

Constructors in net.finmath.montecarlo.process with parameters of type IndependentIncrements

Constructor and Description
EulerSchemeFromProcessModel(IndependentIncrements stochasticDriver) Create an Euler discretization scheme.
EulerSchemeFromProcessModel(IndependentIncrements stochasticDriver, EulerSchemeFromProcessModel.Scheme scheme) Create an Euler discretization scheme.