Uses of Interface
net.finmath.montecarlo.RandomVariableFactory

Packages that use RandomVariableFactory

Package	Description
net.finmath.marketdata2.model	Provides interface specification and implementation of a model, which is essentially a collection of curves.
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.assetderivativevaluation.models	Equity models implementing ProcessModel e.g. by extending AbstractProcessModel.
net.finmath.montecarlo.automaticdifferentiation	Provides classes adding automatic differentiation capabilities to objects relying on RandomVariable objects.
net.finmath.montecarlo.automaticdifferentiation.backward	Provides the implementation of backward automatic differentiation.
net.finmath.montecarlo.automaticdifferentiation.forward	Provides the implementation of forward automatic differentiation.
net.finmath.montecarlo.interestrate.models	Interest rate models implementing ProcessModel e.g. by extending AbstractProcessModel.
net.finmath.montecarlo.interestrate.models.covariance	Contains covariance models and their calibration as plug-ins for the LIBOR market model and volatility and correlation models which may be used to build a covariance model.

Uses of RandomVariableFactory in net.finmath.marketdata2.model

Constructors in net.finmath.marketdata2.model with parameters of type RandomVariableFactory

Constructor	Description
AnalyticModelFromCurvesAndVols(RandomVariableFactory abstractRandomVariableFactory)	Create an empty analytic model using a given AbstractRandomVariableFactory for construction of result types.
AnalyticModelFromCurvesAndVols(RandomVariableFactory abstractRandomVariableFactory, Curve[] curves)	Create an analytic model with the given curves using a given AbstractRandomVariableFactory for construction of result types.

Uses of RandomVariableFactory in net.finmath.modelling.modelfactory

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

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

Uses of RandomVariableFactory in net.finmath.montecarlo

Classes in net.finmath.montecarlo that implement RandomVariableFactory

Modifier and Type	Class	Description
class	AbstractRandomVariableFactory
class	RandomVariableFloatFactory
class	RandomVariableFromArrayFactory	A factory (helper class) to create random variables.
class	RandomVariableLazyEvaluationFactory

Methods in net.finmath.montecarlo with parameters of type RandomVariableFactory

Modifier and Type	Method	Description
static RandomVariable	RandomVariableFactory.getRandomVariableOrDefault(RandomVariableFactory randomVariableFactory, Object value, RandomVariable defaultValue)	Static method for creating random variables from Objects.

Constructors in net.finmath.montecarlo with parameters of type RandomVariableFactory

Constructor	Description
BrownianMotionFromMersenneRandomNumbers(TimeDiscretization timeDiscretization, int numberOfFactors, int numberOfPaths, int seed, RandomVariableFactory abstractRandomVariableFactory)	Construct a Brownian motion.
BrownianMotionFromRandomNumberGenerator(TimeDiscretization timeDiscretization, int numberOfFactors, int numberOfPaths, RandomNumberGenerator randomNumberGenerator, RandomVariableFactory abstractRandomVariableFactory)	Construct a Brownian motion.
BrownianMotionLazyInit(TimeDiscretization timeDiscretization, int numberOfFactors, int numberOfPaths, int seed, RandomVariableFactory abstractRandomVariableFactory)	Deprecated. Construct a Brownian motion.
IndependentIncrementsFromICDF(TimeDiscretization timeDiscretization, int numberOfFactors, int numberOfPaths, int seed, IntFunction<IntFunction<DoubleUnaryOperator>> inverseCumulativeDistributionFunctions, RandomVariableFactory abstractRandomVariableFactory)	Construct the simulation of independent increments.
JumpProcessIncrements(TimeDiscretization timeDiscretization, double[] jumpIntensities, int numberOfPaths, int seed, RandomVariableFactory abstractRandomVariableFactory)	Construct a jump process.

Uses of RandomVariableFactory in net.finmath.montecarlo.assetderivativevaluation.models

Methods in net.finmath.montecarlo.assetderivativevaluation.models that return RandomVariableFactory

Modifier and Type	Method	Description
RandomVariableFactory	DisplacedLognomalModel.getRandomVariableFactory()
RandomVariableFactory	InhomogeneousDisplacedLognomalModel.getRandomVariableFactory()

Constructors in net.finmath.montecarlo.assetderivativevaluation.models with parameters of type RandomVariableFactory

Constructor	Description
BachelierModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility)	Create a Monte-Carlo simulation using given time discretization.
BlackScholesModel(double initialValue, double riskFreeRate, double volatility, RandomVariableFactory abstractRandomVariableFactory)	Create a Monte-Carlo simulation using given time discretization.
BlackScholesModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariableFactory abstractRandomVariableFactory)	Create a Black-Scholes specification implementing AbstractProcessModel.
BlackScholesModelWithCurves(Double initialValue, DiscountCurve discountCurveForForwardRate, Double volatility, DiscountCurve discountCurveForDiscountRate, RandomVariableFactory abstractRandomVariableFactory)	Create a Black-Scholes specification implementing AbstractProcessModel.
BlackScholesModelWithCurves(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariableFactory abstractRandomVariableFactory)	Create a Black-Scholes specification implementing AbstractProcessModel.
DisplacedLognomalModel(RandomVariableFactory randomVariableFactory, double initialValue, double riskFreeRate, double displacement, double volatility)	Create a Monte-Carlo simulation using given time discretization.
DisplacedLognomalModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable displacement, RandomVariable volatility)	Create a Monte-Carlo simulation using given time discretization.
HestonModel(double initialValue, double riskFreeRate, double volatility, double discountRate, double theta, double kappa, double xi, double rho, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create a Heston model.
HestonModel(HestonModelDescriptor descriptor, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create the model from a descriptor.
HestonModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariable theta, RandomVariable kappa, RandomVariable xi, RandomVariable rho, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create a Heston model.
HestonModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariable discountRate, RandomVariable theta, RandomVariable kappa, RandomVariable xi, RandomVariable rho, HestonModel.Scheme scheme, RandomVariableFactory randomVariableFactory)	Create a Heston model.
InhomogeneousDisplacedLognomalModel(RandomVariableFactory randomVariableFactory, double initialValue, double riskFreeRate, double displacement, double volatility, boolean isUseMilsteinCorrection)	Create a blended normal/lognormal model.
InhomogeneousDisplacedLognomalModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable displacement, RandomVariable volatility, boolean isUseMilsteinCorrection)	Create a blended normal/lognormal model.
InhomogenousBachelierModel(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility)
MertonModel(double initialValue, double riskFreeRate, double volatility, double discountRate, double jumpIntensity, double jumpSizeMean, double jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
MertonModel(double initialValue, DiscountCurve discountCurveForForwardRate, double volatility, DiscountCurve discountCurveForDiscountRate, double jumpIntensity, double jumpSizeMean, double jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
MertonModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariable jumpIntensity, RandomVariable jumpSizeMean, RandomVariable jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
MertonModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariable discountRate, RandomVariable jumpIntensity, RandomVariable jumpSizeMean, RandomVariable jumpSizeStDev, RandomVariableFactory randomVariableFactory)	Create a Merton model.
VarianceGammaModel(double initialValue, DiscountCurve discountCurveForForwardRate, DiscountCurve discountCurveForDiscountRate, double sigma, double theta, double nu, RandomVariableFactory randomVariableFactory)	Construct a Variance Gamma model with discount curves for the forward price (i.e. repo rate minus dividend yield) and for discounting.
VarianceGammaModel(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, DiscountCurve discountCurveForDiscountRate, RandomVariable sigma, RandomVariable theta, RandomVariable nu, RandomVariableFactory randomVariableFactory)	Construct a Variance Gamma model with discount curves for the forward price (i.e. repo rate minus dividend yield) and for discounting.
VarianceGammaModel(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable discountRate, RandomVariable sigma, RandomVariable theta, RandomVariable nu, RandomVariableFactory randomVariableFactory)	Construct a Variance Gamma model with constant rates for the forward price (i.e. repo rate minus dividend yield) and for the discount curve.

Uses of RandomVariableFactory in net.finmath.montecarlo.automaticdifferentiation

Subinterfaces of RandomVariableFactory in net.finmath.montecarlo.automaticdifferentiation

Modifier and Type	Interface	Description
interface	RandomVariableDifferentiableFactory	A factory for creating objects implementing net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiable.

Classes in net.finmath.montecarlo.automaticdifferentiation that implement RandomVariableFactory

Modifier and Type	Class	Description
class	AbstractRandomVariableDifferentiableFactory	A random variable factory extending AbstractRandomVariableFactory providing random variables implementing RandomVariableDifferentiable.

Constructors in net.finmath.montecarlo.automaticdifferentiation with parameters of type RandomVariableFactory

Constructor	Description
AbstractRandomVariableDifferentiableFactory(RandomVariableFactory randomVariableFactoryForNonDifferentiable)	Construct an object extending AbstractRandomVariableDifferentiableFactory with a specific AbstractRandomVariableFactory for the storage of values.

Uses of RandomVariableFactory in net.finmath.montecarlo.automaticdifferentiation.backward

Classes in net.finmath.montecarlo.automaticdifferentiation.backward that implement RandomVariableFactory

Modifier and Type	Class	Description
class	RandomVariableDifferentiableAADFactory

Constructors in net.finmath.montecarlo.automaticdifferentiation.backward with parameters of type RandomVariableFactory

Constructor	Description
RandomVariableDifferentiableAADFactory(RandomVariableFactory randomVariableFactoryForNonDifferentiable)
RandomVariableDifferentiableAADFactory(RandomVariableFactory randomVariableFactoryForNonDifferentiable, Map<String,Object> properties)	Create a factory for objects of type RandomVariableDifferentiableAAD.

Uses of RandomVariableFactory in net.finmath.montecarlo.automaticdifferentiation.forward

Classes in net.finmath.montecarlo.automaticdifferentiation.forward that implement RandomVariableFactory

Modifier and Type	Class	Description
class	RandomVariableDifferentiableADFactory

Constructors in net.finmath.montecarlo.automaticdifferentiation.forward with parameters of type RandomVariableFactory

Constructor	Description
RandomVariableDifferentiableADFactory(RandomVariableFactory randomVariableFactoryForNonDifferentiable)

Uses of RandomVariableFactory in net.finmath.montecarlo.interestrate.models

Methods in net.finmath.montecarlo.interestrate.models with parameters of type RandomVariableFactory

Modifier and Type	Method	Description
static HullWhiteModel	HullWhiteModel.of(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, ShortRateVolatilityModel volatilityModel, CalibrationProduct[] calibrationProducts, Map<String,Object> properties)	Creates a Hull-White model which implements LIBORMarketModel.
static LIBORMarketModelFromCovarianceModel	LIBORMarketModelFromCovarianceModel.of(TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, RandomVariableFactory randomVariableFactory, LIBORCovarianceModel covarianceModel, CalibrationProduct[] calibrationProducts, Map<String,?> properties)	Creates a LIBOR Market Model for given covariance with a calibration (if calibration items are given).

Constructors in net.finmath.montecarlo.interestrate.models with parameters of type RandomVariableFactory

Constructor	Description
HullWhiteModel(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, ShortRateVolatilityModel volatilityModel, Map<String,Object> properties)	Creates a Hull-White model which implements LIBORMarketModel.
LIBORMarketModelFromCovarianceModel(TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, RandomVariableFactory randomVariableFactory, LIBORCovarianceModel covarianceModel, Map<String,?> properties)	Creates a LIBOR Market Model for given covariance.
LIBORMarketModelFromCovarianceModel(TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, RandomVariableFactory randomVariableFactory, LIBORCovarianceModel covarianceModel, CalibrationProduct[] calibrationProducts, Map<String,?> properties)	Creates a LIBOR Market Model for given covariance.

Uses of RandomVariableFactory in net.finmath.montecarlo.interestrate.models.covariance

Constructors in net.finmath.montecarlo.interestrate.models.covariance with parameters of type RandomVariableFactory

Constructor	Description
BlendedLocalVolatilityModel(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, double displacement, boolean isCalibrateable)	Displaced diffusion model build on top of a standard covariance model.
BlendedLocalVolatilityModel(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve forwardCurve, double displacement, boolean isCalibrateable)	Displaced diffusion model build on top of a standard covariance model.
ExponentialDecayLocalVolatilityModel(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, double decay, boolean isCalibrateable)	Exponential decay model build on top of a standard covariance model.
ExponentialDecayLocalVolatilityModel(RandomVariableFactory abstractRandomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable decay, boolean isCalibrateable)	Exponential decay model build on top of a standard covariance model.
LIBORVolatilityModelFourParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b, double c, double d, boolean isCalibrateable)	Creates the volatility model σi(tj) = ( a + b * (Ti-tj) ) * exp(-c (Ti-tj)) + d
LIBORVolatilityModelFourParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, RandomVariable c, RandomVariable d, boolean isCalibrateable)	Creates the volatility model σi(tj) = ( a + b * (Ti-tj) ) * exp(-c (Ti-tj)) + d
LIBORVolatilityModelFourParameterExponentialFormIntegrated(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b, double c, double d, boolean isCalibrateable)	Creates the volatility model \[ \sigma_{i}(t_{j}) = \sqrt{ \frac{1}{t_{j+1}-t_{j}} \int_{t_{j}}^{t_{j+1}} \left( ( a + b (T_{i}-t) ) \exp(-c (T_{i}-t)) + d \right)^{2} \ \mathrm{d}t } \text{
LIBORVolatilityModelFromGivenMatrix(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double[][] volatility)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelFromGivenMatrix(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double[][] volatility, boolean isCalibrateable)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelFromGivenMatrix(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility, boolean isCalibrateable)	Creates a simple volatility model using given piece-wise constant values on a given discretization grid.
LIBORVolatilityModelMaturityDependentFourParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double[] a, double[] b, double[] c, double[] d)
LIBORVolatilityModelMaturityDependentFourParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b, double c, double d)
LIBORVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization simulationTimeDiscretization, TimeDiscretization timeToMaturityDiscretization, double[][] volatility, boolean isCalibrateable)
LIBORVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization simulationTimeDiscretization, TimeDiscretization timeToMaturityDiscretization, double[] volatility, boolean isCalibrateable)
LIBORVolatilityModelTimeHomogenousPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization timeToMaturityDiscretization, double[] volatility)	Create a piecewise constant volatility model, where \( \sigma(t,T) = sigma_{i} \) where \( i = \max \{ j : \tau_{j} \leq T-t \} \) and \( \tau_{0}, \tau_{1}, \ldots, \tau_{n-1} \) is a given time discretization.
LIBORVolatilityModelTimeHomogenousPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization timeToMaturityDiscretization, RandomVariable[] volatility)	Create a piecewise constant volatility model, where \( \sigma(t,T) = sigma_{i} \) where \( i = \max \{ j : \tau_{j} \leq T-t \} \) and \( \tau_{0}, \tau_{1}, \ldots, \tau_{n-1} \) is a given time discretization.
LIBORVolatilityModelTwoParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, double a, double b, boolean isCalibrateable)	Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
LIBORVolatilityModelTwoParameterExponentialForm(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, boolean isCalibrateable)	Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, double[] volatility, double[] meanReversion, boolean isVolatilityCalibrateable)
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, double[] volatility, double[] meanReversion, boolean isVolatilityCalibrateable, boolean isMeanReversionCalibrateable)
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable)
ShortRateVolatilityModelPiecewiseConstant(RandomVariableFactory abstractRandomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable, boolean isMeanReversionCalibrateable)