Uses of Interface
net.finmath.stochastic.RandomVariable
Package
Description
Integrated Assessment Models.
Experiments related to the DICE model.
Model components of the DICE model
Provides some static functions, e.g., analytic valuation formulas or functions from linear algebra.
Provides classes to create a calibrated model of curves from a collection of calibration
products and corresponding target values.
Basic methodologies to interpolate of curves and surfaces are provided here.
Provides interface specification and implementation of a model, which is essentially
a collection of curves.
Provides interface specification and implementation of curves, e.g., interest rate
curves like discount curves and forward curves.
Provides interface specification and implementation of products, e.g., calibration products.
Provides classes to build products 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.
Equity models implementing
ProcessModel
e.g.Products which may be valued using an
AssetModelMonteCarloSimulationModel
.Provides classes adding automatic differentiation capabilities to objects relying on RandomVariable objects.
Provides the implementation of backward automatic differentiation.
Provides the implementation of forward automatic differentiation.
Algorithms to perform the calculation of conditional expectations in Monte-Carlo simulations,
also known as "American Monte-Carlo".
Provides classes for Cross-Currency models to be implemented via Monte-Carlo
algorithms from
net.finmath.montecarlo.process
.Provides interfaces and classes needed to generate a Hybrid Asset LIBOR Market Model.
Provides classes which implement financial products which may be
valued using a
net.finmath.montecarlo.hybridassetinterestrate.HybridAssetLIBORModelMonteCarloSimulation
.Provides interfaces and classes needed to generate interest rate models model (using numerical
algorithms from
net.finmath.montecarlo.process
.Interest rate models implementing
ProcessModel
e.g.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.
Provides classes which implement financial products which may be
valued using a
net.finmath.montecarlo.interestrate.LIBORModelMonteCarloSimulationModel
.Provides a set product components which allow to build financial products by composition.
Provides a set of indices which can be used as part of a period.
Provides an interface and a base class for process models, i.e., models providing the parameters for
stochastic processes.
Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.
Components providing the barrier in the Monte-Carlo simulation with barrier.
Components providing the factor drift in the simulation of a proxy simulation scheme.
Products which are model independent, but assume a Monte-Carlo simulation.
Legacy classes related to Monte-Carlo simulation - used for teaching only.
Legacy classes related to Monte-Carlo simulation - used for teaching only.
This package provides classes with numerical algorithm for optimization of
an objective function and a factory to easy construction of the optimizers.
Interfaces specifying operations on random variables.
-
Uses of RandomVariable in net.finmath.climate.models
Modifier and TypeMethodDescriptionClimateModel.getAbatement()
ClimateModel.getAbatementCost()
ClimateModel.getAbatementCosts()
CarbonConcentration.getCarbonConcentrationInAtmosphere()
ClimateModel.getConsumptions()
ClimateModel.getDamage()
ClimateModel.getDamageCost()
ClimateModel.getDamageCosts()
ClimateModel.getEmission()
ClimateModel.getGDP()
ClimateModel.getNumeraire
(double time) ClimateModel.getTemperature
(double time) The temperature (scenario vector) at a given time.Temperature.getTemperatureOfAtmosphere()
ClimateModel.getValue()
The aggregated (discounted) value.ClimateModel.getValues()
The random vector of un-discounted values (utilities).Modifier and TypeMethodDescriptionClimateModel.getAbatementModel()
ClimateModel.getSavingsRateModel()
-
Uses of RandomVariable in net.finmath.climate.models.dice
Modifier and TypeMethodDescriptionDICEModel.getAbatement()
DICEModel.getAbatementCost()
DICEModel.getAbatementCosts()
DICEModel.getConsumptions()
DICEModel.getDamage()
DICEModel.getDamageCost()
DICEModel.getDamageCosts()
DICEModel.getEmission()
DICEModel.getGDP()
DICEModel.getNumeraire
(double time) DICEModel.getTemperature
(double time) DICEModel.getValue()
DICEModel.getValues()
-
Uses of RandomVariable in net.finmath.climate.models.dice.submodels
Modifier and TypeMethodDescriptionCarbonConcentration3DScalar.getCarbonConcentrationInAtmosphere()
Temperature2DScalar.getTemperatureOfAtmosphere()
-
Uses of RandomVariable in net.finmath.functions
Modifier and TypeMethodDescriptionstatic RandomVariable
BachelierModel.bachelierHomogeneousOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierHomogeneousOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierHomogeneousOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{.} \] This implies an effective "Bachelier" integrated variance, being (with \( s = 0 \) \[ 1/T \int_{0}^{T} \sigma^2 exp(2 r (T-t)) \mathrm{d}t \ = \ sigma^2 \frac{exp(2 r (T-0))-exp(2 r (T-T)}{2 r T} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp( r t ) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(-r t) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
AnalyticFormulas.bachelierOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
AnalyticFormulas.blackScholesGeneralizedOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, RandomVariable optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionGamma
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) This static method calculated the gamma of a call option under a Black-Scholes modelstatic RandomVariable
AnalyticFormulas.blackScholesOptionGamma
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) This static method calculated the gamma of a call option under a Black-Scholes modelstatic RandomVariable
AnalyticFormulas.blackScholesOptionValue
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionValue
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionVega
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Black-Scholes model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma S(t)\mathrm{d}W(t) \]static RandomVariable
AnalyticFormulas.blackScholesOptionVega
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Black-Scholes model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma S(t)\mathrm{d}W(t) \]Modifier and TypeMethodDescriptionstatic RandomVariable
BachelierModel.bachelierHomogeneousOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierHomogeneousOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierHomogeneousOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(rt) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma / N(T) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{.} \] This implies an effective "Bachelier" integrated variance, being (with \( s = 0 \) \[ 1/T \int_{0}^{T} \sigma^2 exp(2 r (T-t)) \mathrm{d}t \ = \ sigma^2 \frac{exp(2 r (T-0))-exp(2 r (T-T)}{2 r T} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with constant volatility, i.e., a inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(r (T-t)) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierInhomogeneousOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Inhomogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp( r t ) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma exp(-r t) \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionDelta
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option delta dV(0)/dS(0) of a call option, i.e., the payoff V(T)=max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
AnalyticFormulas.bachelierOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
BachelierModel.bachelierOptionVega
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with numeraire scaled volatility, i.e., a homogeneous Bachelier model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma exp(-r (T-t)) \mathrm{d}W(t) \] Considering the numeraire \( N(t) = exp(-r (T-t)) \), this implies that \( F(t) = S(t)/N(t) \) follows \[ \mathrm{d} F(t) = \sigma \mathrm{d}W(t) \text{.} \]static RandomVariable
AnalyticFormulas.blackScholesGeneralizedOptionValue
(RandomVariable forward, RandomVariable volatility, double optionMaturity, double optionStrike, RandomVariable payoffUnit) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionDelta
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, RandomVariable optionStrike) Calculates the delta of a call option under a Black-Scholes model The method also handles cases where the forward and/or option strike is negative and some limit cases where the forward or the option strike is zero.static RandomVariable
AnalyticFormulas.blackScholesOptionGamma
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) This static method calculated the gamma of a call option under a Black-Scholes modelstatic RandomVariable
AnalyticFormulas.blackScholesOptionGamma
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) This static method calculated the gamma of a call option under a Black-Scholes modelstatic RandomVariable
AnalyticFormulas.blackScholesOptionValue
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionValue
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the Black-Scholes option value of a call, i.e., the payoff max(S(T)-K,0), where S follows a log-normal process with constant log-volatility.static RandomVariable
AnalyticFormulas.blackScholesOptionVega
(RandomVariable initialStockValue, double riskFreeRate, double volatility, double optionMaturity, double optionStrike) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Black-Scholes model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma S(t)\mathrm{d}W(t) \]static RandomVariable
AnalyticFormulas.blackScholesOptionVega
(RandomVariable initialStockValue, RandomVariable riskFreeRate, RandomVariable volatility, double optionMaturity, double optionStrike) Calculates the vega of a call, i.e., the payoff max(S(T)-K,0) P, where S follows a normal process with constant volatility, i.e., a Black-Scholes model \[ \mathrm{d} S(t) = r S(t) \mathrm{d} t + \sigma S(t)\mathrm{d}W(t) \]double
JarqueBeraTest.test
(RandomVariable randomVariable) Return the test statistic of the Jarque-Bera test for a given random variable. -
Uses of RandomVariable in net.finmath.marketdata2.calibration
Modifier and TypeMethodDescriptionParameterAggregation.getParameter()
ParameterObject.getParameter()
Get the current parameter associated with the state of the objects.ParameterTransformation.getParameter
(RandomVariable[] solverParameter) Return the original parameter for the given (unbounded) solver parameter.ParameterTransformation.getSolverParameter
(RandomVariable[] parameter) Return the (unbounded) solver parameter for the given original parameter.Modifier and TypeMethodDescriptionParameterAggregation.getCloneForParameter
(RandomVariable[] value) ParameterObject.getCloneForParameter
(RandomVariable[] value) Create a clone with a modified parameter.Map<E,
RandomVariable[]> ParameterAggregation.getObjectsToModifyForParameter
(RandomVariable[] parameter) ParameterTransformation.getParameter
(RandomVariable[] solverParameter) Return the original parameter for the given (unbounded) solver parameter.ParameterTransformation.getSolverParameter
(RandomVariable[] parameter) Return the (unbounded) solver parameter for the given original parameter.void
ParameterAggregation.setParameter
(RandomVariable[] parameter) void
ParameterObject.setParameter
(RandomVariable[] parameter) Deprecated. -
Uses of RandomVariable in net.finmath.marketdata2.interpolation
Modifier and TypeMethodDescriptionRationalFunctionInterpolation.getValue
(double x) Get an interpolated value for a given argument x.ModifierConstructorDescriptionRationalFunctionInterpolation
(double[] points, RandomVariable[] values) Generate a rational function interpolation from a given set of points.RationalFunctionInterpolation
(double[] points, RandomVariable[] values, RationalFunctionInterpolation.InterpolationMethod interpolationMethod, RationalFunctionInterpolation.ExtrapolationMethod extrapolationMethod) Generate a rational function interpolation from a given set of points using the specified interpolation and extrapolation method. -
Uses of RandomVariable in net.finmath.marketdata2.model
Modifier and TypeMethodDescriptionAnalyticModel.getRandomVariableForConstant
(double value) AnalyticModelFromCurvesAndVols.getRandomVariableForConstant
(double value) -
Uses of RandomVariable in net.finmath.marketdata2.model.curves
Modifier and TypeMethodDescriptionstatic RandomVariable[]
DiscountCurveInterpolation.createZeroRates
(double time, double[] maturities, LIBORModelMonteCarloSimulationModel model) DiscountCurveFromForwardCurve.getDiscountFactor
(double maturity) DiscountCurveFromForwardCurve.getDiscountFactor
(AnalyticModel model, double maturity) DiscountCurveInterface.getDiscountFactor
(double maturity) Returns the discount factor for the corresponding maturity.DiscountCurveInterface.getDiscountFactor
(AnalyticModel model, double maturity) Returns the discount factor for the corresponding maturity.DiscountCurveInterpolation.getDiscountFactor
(double maturity) DiscountCurveInterpolation.getDiscountFactor
(AnalyticModel model, double maturity) ForwardCurveFromDiscountCurve.getForward
(AnalyticModel model, double fixingTime) ForwardCurveFromDiscountCurve.getForward
(AnalyticModel model, double fixingTime, double paymentOffset) ForwardCurveInterface.getForward
(AnalyticModel model, double fixingTime) Returns the forward for the corresponding fixing time.ForwardCurveInterface.getForward
(AnalyticModel model, double fixingTime, double paymentOffset) Returns the forward for the corresponding fixing time and paymentOffset.ForwardCurveInterpolation.getForward
(AnalyticModel model, double fixingTime) ForwardCurveInterpolation.getForward
(AnalyticModel model, double fixingTime, double paymentOffset) Returns the forward for the corresponding fixing time.AbstractForwardCurve.getForwards
(AnalyticModel model, double[] fixingTimes) Returns the forwards for a given vector fixing times.CurveInterpolation.getParameter()
DiscountCurveFromForwardCurve.getParameter()
ForwardCurveFromDiscountCurve.getParameter()
AbstractCurve.getValue
(double time) Curve.getValue
(double time) Returns the value for the time using the interpolation method associated with this curve.Curve.getValue
(AnalyticModel model, double time) Returns the value for the time using the interpolation method associated with this curve within a given context, i.e., a model.CurveInterpolation.getValue
(double time) CurveInterpolation.getValue
(AnalyticModel model, double time) DiscountCurveFromForwardCurve.getValue
(AnalyticModel model, double time) ForwardCurveFromDiscountCurve.getValue
(double time) ForwardCurveFromDiscountCurve.getValue
(AnalyticModel model, double time) AbstractCurve.getValues
(double[] times) Return a vector of values corresponding to a given vector of times.DiscountCurveInterpolation.getZeroRate
(double maturity) Returns the zero rate for a given maturity, i.e., -ln(df(T)) / T where T is the given maturity and df(T) is the discount factor at time $T$.DiscountCurveInterpolation.getZeroRates
(double[] maturities) Returns the zero rates for a given vector maturities.Modifier and TypeMethodDescriptionprotected void
DiscountCurveInterpolation.addDiscountFactor
(double maturity, RandomVariable discountFactor, boolean isParameter) CurveBuilder.addPoint
(double time, RandomVariable value, boolean isParameter) Add a point to the curve.protected void
CurveInterpolation.addPoint
(double time, RandomVariable value, boolean isParameter) Add a point to this curveFromInterpolationPoints.CurveInterpolation.Builder.addPoint
(double time, RandomVariable value, boolean isParameter) protected void
ForwardCurveInterpolation.addPoint
(double time, RandomVariable value, boolean isParameter) static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromAnnualizedZeroRates
(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenAnnualizedZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given annualized zero rates using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromAnnualizedZeroRates
(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenAnnualizedZeroRates, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given annualized zero rates using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors
(String name, double[] times, RandomVariable[] givenDiscountFactors) Create a discount curve from given times and given discount factors using default interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors
(String name, double[] times, RandomVariable[] givenDiscountFactors, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors
(String name, double[] times, RandomVariable[] givenDiscountFactors, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromDiscountFactors
(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenDiscountFactors, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given discount factors using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromZeroRates
(String name, double[] times, RandomVariable[] givenZeroRates) Create a discount curve from given times and given zero rates using default interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromZeroRates
(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromZeroRates
(String name, LocalDate referenceDate, double[] times, RandomVariable[] givenZeroRates, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.static DiscountCurveInterpolation
DiscountCurveInterpolation.createDiscountCurveFromZeroRates
(String name, Date referenceDate, double[] times, RandomVariable[] givenZeroRates, boolean[] isParameter, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity) Create a discount curve from given times and given zero rates using given interpolation and extrapolation methods.static DiscountCurveInterface
DiscountCurveInterpolation.createDiscountFactorsFromForwardRates
(String name, TimeDiscretization tenor, RandomVariable[] forwardRates) Create a discount curve from given time discretization and forward rates.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromDiscountFactors
(String name, double[] times, RandomVariable[] givenDiscountFactors, double paymentOffset) Create a forward curve from given times and discount factors.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, double[] times, RandomVariable[] givenForwards, double paymentOffset) Create a forward curve from given times and given forwards.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, double[] times, RandomVariable[] givenForwards, AnalyticModel model, String discountCurveName, double paymentOffset) Create a forward curve from given times and given forwards with respect to an associated discount curve and payment offset.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, LocalDate referenceDate, String paymentOffsetCode, String interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards) Create a forward curve from given times and given forwards.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, LocalDate referenceDate, String paymentOffsetCode, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards) Create a forward curve from given times and given forwards.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, LocalDate referenceDate, String paymentOffsetCode, BusinessdayCalendar paymentBusinessdayCalendar, BusinessdayCalendar.DateRollConvention paymentDateRollConvention, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards) Create a forward curve from given times and given forwards.static ForwardCurveInterpolation
ForwardCurveInterpolation.createForwardCurveFromForwards
(String name, Date referenceDate, String paymentOffsetCode, BusinessdayCalendar paymentBusinessdayCalendar, BusinessdayCalendar.DateRollConvention paymentDateRollConvention, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, ForwardCurveInterpolation.InterpolationEntityForward interpolationEntityForward, String discountCurveName, AnalyticModel model, double[] times, RandomVariable[] givenForwards) Create a forward curve from given times and given forwards.AbstractCurve.getCloneForParameter
(RandomVariable[] value) Curve.getCloneForParameter
(RandomVariable[] value) CurveInterpolation.getCloneForParameter
(RandomVariable[] parameter) void
CurveInterpolation.setParameter
(RandomVariable[] parameter) void
DiscountCurveFromForwardCurve.setParameter
(RandomVariable[] parameter) ModifierConstructorDescriptionCurveInterpolation
(String name, LocalDate referenceDate, CurveInterpolation.InterpolationMethod interpolationMethod, CurveInterpolation.ExtrapolationMethod extrapolationMethod, CurveInterpolation.InterpolationEntity interpolationEntity, double[] times, RandomVariable[] values) Create a curveFromInterpolationPoints with a given name, reference date and an interpolation method from given points -
Uses of RandomVariable in net.finmath.marketdata2.products
Modifier and TypeMethodDescriptionstatic RandomVariable
Swap.getForwardSwapRate
(Schedule fixSchedule, Schedule floatSchedule, ForwardCurveInterface forwardCurve) static RandomVariable
Swap.getForwardSwapRate
(Schedule fixSchedule, Schedule floatSchedule, ForwardCurveInterface forwardCurve, AnalyticModel model) static RandomVariable
Swap.getForwardSwapRate
(TimeDiscretization fixTenor, TimeDiscretization floatTenor, ForwardCurveInterface forwardCurve) static RandomVariable
Swap.getForwardSwapRate
(TimeDiscretization fixTenor, TimeDiscretization floatTenor, ForwardCurveInterface forwardCurve, DiscountCurveInterface discountCurve) Deposit.getRate
(AnalyticModel model) Return the deposit rate implied by the given model's curve.ForwardRateAgreement.getRate
(AnalyticModel model) Return the par FRA rate for a given curve.static RandomVariable
SwapAnnuity.getSwapAnnuity
(double evaluationTime, Schedule schedule, DiscountCurveInterface discountCurve, AnalyticModel model) Function to calculate an (idealized) swap annuity for a given schedule and discount curve.static RandomVariable
SwapAnnuity.getSwapAnnuity
(Schedule schedule, DiscountCurveInterface discountCurve) Function to calculate an (idealized) swap annuity for a given schedule and discount curve.static RandomVariable
SwapAnnuity.getSwapAnnuity
(Schedule schedule, ForwardCurveInterface forwardCurve) Function to calculate an (idealized) single curve swap annuity for a given schedule and forward curve.static RandomVariable
SwapAnnuity.getSwapAnnuity
(TimeDiscretization tenor, DiscountCurveInterface discountCurve) Function to calculate an (idealized) swap annuity for a given schedule and discount curve.static RandomVariable
SwapAnnuity.getSwapAnnuity
(TimeDiscretization tenor, ForwardCurveInterface forwardCurve) Function to calculate an (idealized) single curve swap annuity for a given schedule and forward curve.AbstractAnalyticProduct.getValue
(AnalyticModel model) AnalyticProduct.getValue
(double evaluationTime, AnalyticModel model) Return the valuation of the product using the given model.Cashflow.getValue
(double evaluationTime, AnalyticModel model) Deposit.getValue
(double evaluationTime, AnalyticModel model) Forward.getValue
(double evaluationTime, AnalyticModel model) ForwardRateAgreement.getValue
(double evaluationTime, AnalyticModel model) MarketForwardRateAgreement.getValue
(double evaluationTime, AnalyticModel model) Performance.getValue
(double evaluationTime, AnalyticModel model) Portfolio.getValue
(double evaluationTime, AnalyticModel model) Swap.getValue
(double evaluationTime, AnalyticModel model) SwapAnnuity.getValue
(double evaluationTime, AnalyticModel model) SwapLeg.getValue
(double evaluationTime, AnalyticModel model) -
Uses of RandomVariable in net.finmath.modelling.productfactory
Modifier and TypeMethodDescriptionInterestRateMonteCarloProductFactory.SwapMonteCarlo.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) InterestRateMonteCarloProductFactory.SwaptionPhysicalMonteCarlo.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) -
Uses of RandomVariable in net.finmath.montecarlo
Modifier and TypeClassDescriptionclass
The class RandomVariableFromDoubleArray represents a random variable being the evaluation of a stochastic process at a certain time within a Monte-Carlo simulation.class
The class RandomVariableFromFloatArray represents a random variable being the evaluation of a stochastic process at a certain time within a Monte-Carlo simulation.class
Implements a Monte-Carlo random variable (likeRandomVariableFromDoubleArray
using late evaluation of Java 8 streams Accesses performed exclusively through the interfaceRandomVariable
is thread safe (and does not mutate the class).Modifier and TypeMethodDescriptionRandomVariableFromDoubleArray.abs()
RandomVariableFromFloatArray.abs()
RandomVariableLazyEvaluation.abs()
RandomVariableFromDoubleArray.accrue
(RandomVariable rate, double periodLength) RandomVariableFromFloatArray.accrue
(RandomVariable rate, double periodLength) RandomVariableLazyEvaluation.accrue
(RandomVariable rate, double periodLength) RandomVariableFromDoubleArray.add
(double value) RandomVariableFromDoubleArray.add
(RandomVariable randomVariable) RandomVariableFromFloatArray.add
(double value) RandomVariableFromFloatArray.add
(RandomVariable randomVariable) RandomVariableLazyEvaluation.add
(double value) RandomVariableLazyEvaluation.add
(RandomVariable randomVariable) RandomVariableFromDoubleArray.addProduct
(RandomVariable factor1, double factor2) RandomVariableFromDoubleArray.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableFromFloatArray.addProduct
(RandomVariable factor1, double factor2) RandomVariableFromFloatArray.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableLazyEvaluation.addProduct
(RandomVariable factor1, double factor2) RandomVariableLazyEvaluation.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableFromDoubleArray.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromFloatArray.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableLazyEvaluation.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromDoubleArray.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) RandomVariableFromFloatArray.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) RandomVariableFromDoubleArray.apply
(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2) RandomVariableFromDoubleArray.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableFromDoubleArray.apply
(DoubleUnaryOperator operator) RandomVariableFromDoubleArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableFromFloatArray.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableFromFloatArray.apply
(DoubleUnaryOperator operator) RandomVariableFromFloatArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableLazyEvaluation.apply
(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2) RandomVariableLazyEvaluation.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableLazyEvaluation.apply
(DoubleUnaryOperator operator) RandomVariableLazyEvaluation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableFromDoubleArray.average()
RandomVariableFromFloatArray.average()
RandomVariableLazyEvaluation.average()
RandomVariableFromDoubleArray.bus
(double value) RandomVariableFromDoubleArray.bus
(RandomVariable randomVariable) RandomVariableFromFloatArray.bus
(double value) RandomVariableFromFloatArray.bus
(RandomVariable randomVariable) RandomVariableLazyEvaluation.bus
(RandomVariable randomVariable) RandomVariableFromDoubleArray.cache()
RandomVariableFromFloatArray.cache()
RandomVariableLazyEvaluation.cache()
RandomVariableFromDoubleArray.cap
(double cap) RandomVariableFromDoubleArray.cap
(RandomVariable randomVariable) RandomVariableFromFloatArray.cap
(double cap) RandomVariableFromFloatArray.cap
(RandomVariable randomVariable) RandomVariableLazyEvaluation.cap
(double cap) RandomVariableLazyEvaluation.cap
(RandomVariable cap) RandomVariableFromDoubleArray.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableFromFloatArray.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableLazyEvaluation.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableFromDoubleArray.cos()
RandomVariableFromFloatArray.cos()
RandomVariableLazyEvaluation.cos()
AbstractRandomVariableFactory.createRandomVariable
(double value) abstract RandomVariable
AbstractRandomVariableFactory.createRandomVariable
(double time, double value) abstract RandomVariable
AbstractRandomVariableFactory.createRandomVariable
(double time, double[] values) RandomVariableFactory.createRandomVariable
(double value) Create a (deterministic) random variable from a constant.default RandomVariable
RandomVariableFactory.createRandomVariable
(double[] values) RandomVariableFactory.createRandomVariable
(double time, double value) Create a (deterministic) random variable from a constant using a specific filtration time.RandomVariableFactory.createRandomVariable
(double time, double[] values) Create a random variable from an array using a specific filtration time.RandomVariableFloatFactory.createRandomVariable
(double time, double value) RandomVariableFloatFactory.createRandomVariable
(double time, double[] values) RandomVariableFromArrayFactory.createRandomVariable
(double value) RandomVariableFromArrayFactory.createRandomVariable
(double time, double value) RandomVariableFromArrayFactory.createRandomVariable
(double time, double[] values) RandomVariableLazyEvaluationFactory.createRandomVariable
(double time, double value) RandomVariableLazyEvaluationFactory.createRandomVariable
(double time, double[] values) AbstractRandomVariableFactory.createRandomVariableArray
(double[] values) RandomVariableFactory.createRandomVariableArray
(double[] values) Create an array of (deterministic) random variables from an array of constants.RandomVariable[][]
AbstractRandomVariableFactory.createRandomVariableMatrix
(double[][] values) RandomVariable[][]
RandomVariableFactory.createRandomVariableMatrix
(double[][] values) Create a matrix of (deterministic) random variables from an matrix of constants.RandomVariableFromDoubleArray.discount
(RandomVariable rate, double periodLength) RandomVariableFromFloatArray.discount
(RandomVariable rate, double periodLength) RandomVariableLazyEvaluation.discount
(RandomVariable rate, double periodLength) RandomVariableFromDoubleArray.div
(double value) RandomVariableFromDoubleArray.div
(RandomVariable randomVariable) RandomVariableFromFloatArray.div
(double value) RandomVariableFromFloatArray.div
(RandomVariable randomVariable) RandomVariableLazyEvaluation.div
(double value) RandomVariableLazyEvaluation.div
(RandomVariable randomVariable) RandomVariableLazyEvaluation.exp()
RandomVariableLazyEvaluation.expand
(int numberOfPaths) RandomVariableFromDoubleArray.floor
(double floor) RandomVariableFromDoubleArray.floor
(RandomVariable randomVariable) RandomVariableFromFloatArray.floor
(double floor) RandomVariableFromFloatArray.floor
(RandomVariable randomVariable) RandomVariableLazyEvaluation.floor
(double floor) RandomVariableLazyEvaluation.floor
(RandomVariable floor) BrownianBridge.getBrownianIncrement
(int timeIndex, int factor) default RandomVariable
BrownianMotion.getBrownianIncrement
(double time, int factor) Return the Brownian increment for a given timeIndex.BrownianMotion.getBrownianIncrement
(int timeIndex, int factor) Return the Brownian increment for a given timeIndex.BrownianMotionFromMersenneRandomNumbers.getBrownianIncrement
(int timeIndex, int factor) BrownianMotionFromRandomNumberGenerator.getBrownianIncrement
(int timeIndex, int factor) BrownianMotionView.getBrownianIncrement
(int timeIndex, int factor) BrownianMotionWithControlVariate.getBrownianIncrement
(int timeIndex, int factorIndex) CorrelatedBrownianMotion.getBrownianIncrement
(int timeIndex, int factor) RandomVariableFromDoubleArray.getConditionalExpectation
(ConditionalExpectationEstimator conditionalExpectationOperator) RandomVariableFromFloatArray.getConditionalExpectation
(ConditionalExpectationEstimator conditionalExpectationOperator) BrownianBridge.getIncrement
(int timeIndex) BrownianBridge.getIncrement
(int timeIndex, int factor) default RandomVariable
BrownianMotion.getIncrement
(int timeIndex, int factor) BrownianMotionFromMersenneRandomNumbers.getIncrement
(int timeIndex, int factor) BrownianMotionFromRandomNumberGenerator.getIncrement
(int timeIndex, int factor) BrownianMotionView.getIncrement
(int timeIndex, int factor) BrownianMotionWithControlVariate.getIncrement
(int timeIndex, int factor) CorrelatedBrownianMotion.getIncrement
(int timeIndex, int factor) GammaProcess.getIncrement
(int timeIndex, int factor) default RandomVariable[]
IndependentIncrements.getIncrement
(int timeIndex) Return the increment for a given timeIndex.IndependentIncrements.getIncrement
(int timeIndex, int factor) Return the increment for a given timeIndex and given factor.IndependentIncrementsFromICDF.getIncrement
(int timeIndex, int factor) JumpProcessIncrements.getIncrement
(int timeIndex, int factor) MertonJumpProcess.getIncrement
(int timeIndex, int factor) VarianceGammaProcess.getIncrement
(int timeIndex, int factor) MonteCarloSimulationModel.getMonteCarloWeights
(double time) This method returns the weights of a weighted Monte Carlo method (the probability density).MonteCarloSimulationModel.getMonteCarloWeights
(int timeIndex) This method returns the weights of a weighted Monte Carlo method (the probability density).BrownianBridge.getRandomVariableForConstant
(double value) BrownianMotion.getRandomVariableForConstant
(double value) Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.BrownianMotionFromMersenneRandomNumbers.getRandomVariableForConstant
(double value) BrownianMotionFromRandomNumberGenerator.getRandomVariableForConstant
(double value) BrownianMotionView.getRandomVariableForConstant
(double value) BrownianMotionWithControlVariate.getRandomVariableForConstant
(double value) CorrelatedBrownianMotion.getRandomVariableForConstant
(double value) GammaProcess.getRandomVariableForConstant
(double value) IndependentIncrements.getRandomVariableForConstant
(double value) Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.IndependentIncrementsFromICDF.getRandomVariableForConstant
(double value) JumpProcessIncrements.getRandomVariableForConstant
(double value) MertonJumpProcess.getRandomVariableForConstant
(double value) MonteCarloSimulationModel.getRandomVariableForConstant
(double value) Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by thisMonteCarloSimulationModel
.VarianceGammaProcess.getRandomVariableForConstant
(double value) static RandomVariable
RandomVariableFactory.getRandomVariableOrDefault
(RandomVariableFactory randomVariableFactory, Object value, RandomVariable defaultValue) Static method for creating random variables from Objects.abstract RandomVariable
AbstractMonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) MonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.RandomVariableFromDoubleArray.invert()
RandomVariableFromFloatArray.invert()
RandomVariableLazyEvaluation.invert()
RandomVariableFromDoubleArray.isNaN()
RandomVariableFromFloatArray.isNaN()
RandomVariableLazyEvaluation.isNaN()
RandomVariableLazyEvaluation.log()
RandomVariableFromDoubleArray.mult
(double value) RandomVariableFromDoubleArray.mult
(RandomVariable randomVariable) RandomVariableFromFloatArray.mult
(double value) RandomVariableFromFloatArray.mult
(RandomVariable randomVariable) RandomVariableLazyEvaluation.mult
(double value) RandomVariableLazyEvaluation.mult
(RandomVariable randomVariable) RandomVariableFromDoubleArray.pow
(double exponent) RandomVariableFromFloatArray.pow
(double exponent) RandomVariableLazyEvaluation.pow
(double exponent) RandomVariableFromDoubleArray.sin()
RandomVariableFromFloatArray.sin()
RandomVariableLazyEvaluation.sin()
RandomVariableFromDoubleArray.sqrt()
RandomVariableFromFloatArray.sqrt()
RandomVariableLazyEvaluation.sqrt()
RandomVariableFromDoubleArray.squared()
RandomVariableFromFloatArray.squared()
RandomVariableLazyEvaluation.squared()
RandomVariableFromDoubleArray.sub
(double value) RandomVariableFromDoubleArray.sub
(RandomVariable randomVariable) RandomVariableFromFloatArray.sub
(double value) RandomVariableFromFloatArray.sub
(RandomVariable randomVariable) RandomVariableLazyEvaluation.sub
(double value) RandomVariableLazyEvaluation.sub
(RandomVariable randomVariable) RandomVariableFromDoubleArray.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromFloatArray.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableLazyEvaluation.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromDoubleArray.vid
(double value) RandomVariableFromDoubleArray.vid
(RandomVariable randomVariable) RandomVariableFromFloatArray.vid
(double value) RandomVariableFromFloatArray.vid
(RandomVariable randomVariable) RandomVariableLazyEvaluation.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionRandomVariableFromDoubleArray.accrue
(RandomVariable rate, double periodLength) RandomVariableFromFloatArray.accrue
(RandomVariable rate, double periodLength) RandomVariableLazyEvaluation.accrue
(RandomVariable rate, double periodLength) RandomVariableFromDoubleArray.add
(RandomVariable randomVariable) RandomVariableFromFloatArray.add
(RandomVariable randomVariable) RandomVariableLazyEvaluation.add
(RandomVariable randomVariable) RandomVariableFromDoubleArray.addProduct
(RandomVariable factor1, double factor2) RandomVariableFromDoubleArray.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableFromFloatArray.addProduct
(RandomVariable factor1, double factor2) RandomVariableFromFloatArray.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableLazyEvaluation.addProduct
(RandomVariable factor1, double factor2) RandomVariableLazyEvaluation.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableFromDoubleArray.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromFloatArray.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableLazyEvaluation.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromDoubleArray.apply
(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2) RandomVariableFromDoubleArray.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableFromDoubleArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableFromFloatArray.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableFromFloatArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableLazyEvaluation.apply
(DoubleBinaryOperator operatorOuter, DoubleBinaryOperator operatorInner, RandomVariable argument1, RandomVariable argument2) RandomVariableLazyEvaluation.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableLazyEvaluation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableFromDoubleArray.bus
(RandomVariable randomVariable) RandomVariableFromFloatArray.bus
(RandomVariable randomVariable) RandomVariableLazyEvaluation.bus
(RandomVariable randomVariable) RandomVariableFromDoubleArray.cap
(RandomVariable randomVariable) RandomVariableFromFloatArray.cap
(RandomVariable randomVariable) RandomVariableLazyEvaluation.cap
(RandomVariable cap) RandomVariableFromDoubleArray.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableFromFloatArray.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableLazyEvaluation.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableFromDoubleArray.discount
(RandomVariable rate, double periodLength) RandomVariableFromFloatArray.discount
(RandomVariable rate, double periodLength) RandomVariableLazyEvaluation.discount
(RandomVariable rate, double periodLength) RandomVariableFromDoubleArray.div
(RandomVariable randomVariable) RandomVariableFromFloatArray.div
(RandomVariable randomVariable) RandomVariableLazyEvaluation.div
(RandomVariable randomVariable) boolean
RandomVariableFromDoubleArray.equals
(RandomVariable randomVariable) boolean
RandomVariableFromFloatArray.equals
(RandomVariable randomVariable) boolean
RandomVariableLazyEvaluation.equals
(RandomVariable randomVariable) RandomVariableFromDoubleArray.floor
(RandomVariable randomVariable) RandomVariableFromFloatArray.floor
(RandomVariable randomVariable) RandomVariableLazyEvaluation.floor
(RandomVariable floor) double
RandomVariableFromDoubleArray.getAverage
(RandomVariable probabilities) double
RandomVariableFromFloatArray.getAverage
(RandomVariable probabilities) double
RandomVariableLazyEvaluation.getAverage
(RandomVariable probabilities) double
RandomVariableFromDoubleArray.getQuantile
(double quantile, RandomVariable probabilities) double
RandomVariableFromFloatArray.getQuantile
(double quantile, RandomVariable probabilities) double
RandomVariableLazyEvaluation.getQuantile
(double quantile, RandomVariable probabilities) static RandomVariable
RandomVariableFactory.getRandomVariableOrDefault
(RandomVariableFactory randomVariableFactory, Object value, RandomVariable defaultValue) Static method for creating random variables from Objects.double
RandomVariableFromDoubleArray.getStandardDeviation
(RandomVariable probabilities) double
RandomVariableFromFloatArray.getStandardDeviation
(RandomVariable probabilities) double
RandomVariableLazyEvaluation.getStandardDeviation
(RandomVariable probabilities) double
RandomVariableFromDoubleArray.getStandardError
(RandomVariable probabilities) double
RandomVariableFromFloatArray.getStandardError
(RandomVariable probabilities) double
RandomVariableLazyEvaluation.getStandardError
(RandomVariable probabilities) double
RandomVariableFromDoubleArray.getVariance
(RandomVariable probabilities) double
RandomVariableFromFloatArray.getVariance
(RandomVariable probabilities) double
RandomVariableLazyEvaluation.getVariance
(RandomVariable probabilities) RandomVariableFromDoubleArray.mult
(RandomVariable randomVariable) RandomVariableFromFloatArray.mult
(RandomVariable randomVariable) RandomVariableLazyEvaluation.mult
(RandomVariable randomVariable) RandomVariableFromDoubleArray.sub
(RandomVariable randomVariable) RandomVariableFromFloatArray.sub
(RandomVariable randomVariable) RandomVariableLazyEvaluation.sub
(RandomVariable randomVariable) RandomVariableFromDoubleArray.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromFloatArray.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableLazyEvaluation.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableFromDoubleArray.vid
(RandomVariable randomVariable) RandomVariableFromFloatArray.vid
(RandomVariable randomVariable) RandomVariableLazyEvaluation.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionRandomVariableFromDoubleArray.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) RandomVariableFromFloatArray.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) ModifierConstructorDescriptionBrownianBridge
(BrownianMotion generator, RandomVariable[] start, RandomVariable[] end) BrownianBridge
(TimeDiscretization timeDiscretization, int numberOfPaths, int seed, RandomVariable[] start, RandomVariable[] end) Construct a Brownian bridge, bridging from a given start to a given end.BrownianBridge
(TimeDiscretization timeDiscretization, int numberOfPaths, int seed, RandomVariable start, RandomVariable end) Construct a Brownian bridge, bridging from a given start to a given end.Create a random variable from a given other implementation ofRandomVariable
.RandomVariableFromDoubleArray
(RandomVariable value, DoubleUnaryOperator function) Create a random variable by applying a function to a given other implementation ofRandomVariable
.Create a random variable from a given other implementation ofRandomVariable
.RandomVariableFromFloatArray
(RandomVariable value, DoubleUnaryOperator function) Create a random variable by applying a function to a given other implementation ofRandomVariable
.Create a random variable from a given other implementation ofRandomVariable
.RandomVariableLazyEvaluation
(RandomVariable value, DoubleUnaryOperator function) Create a random variable by applying a function to a given other implementation ofRandomVariable
. -
Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation
Modifier and TypeMethodDescriptionMonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) AssetModelMonteCarloSimulationModel.getAssetValue
(double time, int assetIndex) Returns the random variable representing the asset's value at a given time for a given asset.AssetModelMonteCarloSimulationModel.getAssetValue
(int timeIndex, int assetIndex) Returns the random variable representing the asset's value at a given time for a given asset.MonteCarloAssetModel.getAssetValue
(double time, int assetIndex) MonteCarloAssetModel.getAssetValue
(int timeIndex, int assetIndex) MonteCarloBlackScholesModel.getAssetValue
(double time, int assetIndex) MonteCarloMertonModel.getAssetValue
(double time, int assetIndex) MonteCarloMertonModel.getAssetValue
(int timeIndex, int assetIndex) MonteCarloMultiAssetBlackScholesModel.getAssetValue
(double time, int assetIndex) MonteCarloMultiAssetBlackScholesModel.getAssetValue
(int timeIndex, int assetIndex) MonteCarloVarianceGammaModel.getAssetValue
(double time, int assetIndex) MonteCarloVarianceGammaModel.getAssetValue
(int timeIndex, int assetIndex) MonteCarloMultiAssetBlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloMultiAssetBlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) MonteCarloMultiAssetBlackScholesModel.getInitialState
(MonteCarloProcess process) MonteCarloAssetModel.getMonteCarloWeights
(double time) MonteCarloAssetModel.getMonteCarloWeights
(int timeIndex) MonteCarloMertonModel.getMonteCarloWeights
(double time) MonteCarloMertonModel.getMonteCarloWeights
(int timeIndex) MonteCarloMultiAssetBlackScholesModel.getMonteCarloWeights
(double time) MonteCarloMultiAssetBlackScholesModel.getMonteCarloWeights
(int timeIndex) MonteCarloVarianceGammaModel.getMonteCarloWeights
(double time) MonteCarloVarianceGammaModel.getMonteCarloWeights
(int timeIndex) AssetModelMonteCarloSimulationModel.getNumeraire
(double time) Returns the numeraire associated with the valuation measure used by this model.AssetModelMonteCarloSimulationModel.getNumeraire
(int timeIndex) Returns the numeraire associated with the valuation measure used by this model.MonteCarloAssetModel.getNumeraire
(double time) MonteCarloAssetModel.getNumeraire
(int timeIndex) MonteCarloMertonModel.getNumeraire
(double time) MonteCarloMertonModel.getNumeraire
(int timeIndex) MonteCarloMultiAssetBlackScholesModel.getNumeraire
(double time) MonteCarloMultiAssetBlackScholesModel.getNumeraire
(int timeIndex) MonteCarloMultiAssetBlackScholesModel.getNumeraire
(MonteCarloProcess process, double time) MonteCarloVarianceGammaModel.getNumeraire
(double time) MonteCarloVarianceGammaModel.getNumeraire
(int timeIndex) MonteCarloAssetModel.getRandomVariableForConstant
(double value) MonteCarloMertonModel.getRandomVariableForConstant
(double value) MonteCarloMultiAssetBlackScholesModel.getRandomVariableForConstant
(double value) MonteCarloVarianceGammaModel.getRandomVariableForConstant
(double value) Modifier and TypeMethodDescriptionMonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloMultiAssetBlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloMultiAssetBlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloMultiAssetBlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) -
Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation.models
Modifier and TypeMethodDescriptionBachelierModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModelWithCurves.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) DisplacedLognomalModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HestonModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogeneousDisplacedLognomalModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogenousBachelierModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MertonModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MultiAssetBlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) VarianceGammaModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BachelierModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModelWithCurves.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) DisplacedLognomalModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HestonModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogeneousDisplacedLognomalModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogenousBachelierModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MertonModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MultiAssetBlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) VarianceGammaModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) VarianceGammaModel.getDiscountRate()
DisplacedLognomalModel.getDisplacement()
InhomogeneousDisplacedLognomalModel.getDisplacement()
BachelierModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BlackScholesModelWithCurves.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) DisplacedLognomalModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HestonModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) InhomogeneousDisplacedLognomalModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) InhomogenousBachelierModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MertonModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MultiAssetBlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) VarianceGammaModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BachelierModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlackScholesModelWithCurves.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) DisplacedLognomalModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) HestonModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) InhomogeneousDisplacedLognomalModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) InhomogenousBachelierModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) MertonModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) MultiAssetBlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) VarianceGammaModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) BachelierModel.getImpliedBachelierVolatility
(double maturity) InhomogenousBachelierModel.getImpliedBachelierVolatility
(double maturity) BachelierModel.getInitialState
(MonteCarloProcess process) BlackScholesModel.getInitialState
(MonteCarloProcess process) BlackScholesModelWithCurves.getInitialState
(MonteCarloProcess process) DisplacedLognomalModel.getInitialState
(MonteCarloProcess process) HestonModel.getInitialState
(MonteCarloProcess process) InhomogeneousDisplacedLognomalModel.getInitialState
(MonteCarloProcess process) InhomogenousBachelierModel.getInitialState
(MonteCarloProcess process) MertonModel.getInitialState
(MonteCarloProcess process) MultiAssetBlackScholesModel.getInitialState
(MonteCarloProcess process) VarianceGammaModel.getInitialState
(MonteCarloProcess process) BachelierModel.getInitialValue()
Returns the initial value parameter of this model.BlackScholesModel.getInitialValue
(MonteCarloProcess process) Return the initial value of this model.BlackScholesModelWithCurves.getInitialValue
(MonteCarloProcess process) Return the initial value of this model.DisplacedLognomalModel.getInitialValue()
HestonModel.getInitialValue()
InhomogeneousDisplacedLognomalModel.getInitialValue()
InhomogenousBachelierModel.getInitialValue()
Returns the initial value parameter of this model.MertonModel.getJumpIntensity()
MertonModel.getJumpSizeMean()
MertonModel.getJumpSizeStdDev()
HestonModel.getKappa()
VarianceGammaModel.getNu()
BachelierModel.getNumeraire
(MonteCarloProcess process, double time) BlackScholesModel.getNumeraire
(MonteCarloProcess process, double time) BlackScholesModelWithCurves.getNumeraire
(MonteCarloProcess process, double time) DisplacedLognomalModel.getNumeraire
(MonteCarloProcess process, double time) HestonModel.getNumeraire
(MonteCarloProcess process, double time) InhomogeneousDisplacedLognomalModel.getNumeraire
(MonteCarloProcess process, double time) InhomogenousBachelierModel.getNumeraire
(MonteCarloProcess process, double time) MertonModel.getNumeraire
(MonteCarloProcess process, double time) MultiAssetBlackScholesModel.getNumeraire
(MonteCarloProcess process, double time) VarianceGammaModel.getNumeraire
(MonteCarloProcess process, double time) BachelierModel.getRandomVariableForConstant
(double value) BlackScholesModel.getRandomVariableForConstant
(double value) BlackScholesModelWithCurves.getRandomVariableForConstant
(double value) DisplacedLognomalModel.getRandomVariableForConstant
(double value) HestonModel.getRandomVariableForConstant
(double value) InhomogeneousDisplacedLognomalModel.getRandomVariableForConstant
(double value) InhomogenousBachelierModel.getRandomVariableForConstant
(double value) MertonModel.getRandomVariableForConstant
(double value) MultiAssetBlackScholesModel.getRandomVariableForConstant
(double value) VarianceGammaModel.getRandomVariableForConstant
(double value) HestonModel.getRho()
BachelierModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.BlackScholesModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.DisplacedLognomalModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.HestonModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.InhomogeneousDisplacedLognomalModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.InhomogenousBachelierModel.getRiskFreeRate()
Returns the risk free rate parameter of this model.MertonModel.getRiskFreeRate()
VarianceGammaModel.getRiskFreeRate()
VarianceGammaModel.getSigma()
HestonModel.getTheta()
VarianceGammaModel.getTheta()
BachelierModel.getVolatility()
Returns the volatility parameter of this model.BlackScholesModel.getVolatility()
Returns the volatility parameter of this model.BlackScholesModelWithCurves.getVolatility()
Returns the volatility parameter of this model.DisplacedLognomalModel.getVolatility()
Returns the volatility parameter of this model.HestonModel.getVolatility()
Returns the volatility parameter of this model.InhomogeneousDisplacedLognomalModel.getVolatility()
Returns the volatility parameter of this model.InhomogenousBachelierModel.getVolatility()
Returns the volatility parameter of this model.MertonModel.getVolatility()
HestonModel.getXi()
Modifier and TypeMethodDescriptionBachelierModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModelWithCurves.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) DisplacedLognomalModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HestonModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogeneousDisplacedLognomalModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogenousBachelierModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MertonModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MultiAssetBlackScholesModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) VarianceGammaModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BachelierModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BlackScholesModelWithCurves.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) DisplacedLognomalModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HestonModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogeneousDisplacedLognomalModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) InhomogenousBachelierModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MertonModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) MultiAssetBlackScholesModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) VarianceGammaModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) BachelierModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BlackScholesModelWithCurves.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) DisplacedLognomalModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HestonModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) InhomogeneousDisplacedLognomalModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) InhomogenousBachelierModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MertonModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MultiAssetBlackScholesModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) VarianceGammaModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) BachelierModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlackScholesModelWithCurves.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) DisplacedLognomalModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) HestonModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) InhomogeneousDisplacedLognomalModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) InhomogenousBachelierModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) MertonModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) MultiAssetBlackScholesModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) VarianceGammaModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) ModifierConstructorDescriptionBachelierModel
(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility) Create a Monte-Carlo simulation using given time discretization.BlackScholesModel
(RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable volatility, RandomVariableFactory randomVariableFactory) Create a Black-Scholes specification implementing AbstractProcessModel.BlackScholesModelWithCurves
(RandomVariable initialValue, DiscountCurve discountCurveForForwardRate, RandomVariable volatility, DiscountCurve discountCurveForDiscountRate, RandomVariableFactory randomVariableFactory) Create a Black-Scholes specification implementing AbstractProcessModel.DisplacedLognomalModel
(RandomVariableFactory randomVariableFactory, RandomVariable initialValue, RandomVariable riskFreeRate, RandomVariable displacement, RandomVariable volatility) Create a Monte-Carlo simulation using given time discretization.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, 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
(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
(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.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. -
Uses of RandomVariable in net.finmath.montecarlo.assetderivativevaluation.products
Modifier and TypeMethodDescriptionEuropeanOptionWithBoundary.getBoundaryAdjustment
(double fromTime, double toTime, AssetModelMonteCarloSimulationModel model, RandomVariable continuationValues) BermudanOption.getLastValuationContinuationValueAtExerciseTime()
BermudanOption.getLastValuationContinuationValueEstimatedAtExerciseTime()
BermudanOption.getLastValuationExerciseTime()
BermudanOption.getLastValuationExerciseValueAtExerciseTime()
abstract RandomVariable
AbstractAssetMonteCarloProduct.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) AbstractAssetMonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) AsianOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.AssetMonteCarloProduct.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) BasketOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.BermudanDigitalOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.BermudanOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.BlackScholesDeltaHedgedPortfolio.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) BlackScholesHedgedPortfolio.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) DeltaHedgedPortfolioWithAAD.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) DigitalOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.DigitalOptionDeltaLikelihood.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.EuropeanOption.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.EuropeanOptionDeltaLikelihood.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.EuropeanOptionDeltaPathwise.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.EuropeanOptionDeltaPathwiseForGeometricModel.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.EuropeanOptionThetaPathwise.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) EuropeanOptionVegaPathwise.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) EuropeanOptionWithBoundary.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.FiniteDifferenceDeltaHedgedPortfolio.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) FiniteDifferenceHedgedPortfolio.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) ForwardAgreement.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ForwardAgreementWithFundingRequirement.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.LocalRiskMinimizingHedgePortfolio.getValue
(double evaluationTime, AssetModelMonteCarloSimulationModel model) Modifier and TypeMethodDescriptionEuropeanOptionWithBoundary.ConstantBarrier.getBarrierDirection
(int timeIndex, RandomVariable[] realizationPredictor) EuropeanOptionWithBoundary.ConstantBarrier.getBarrierLevel
(int timeIndex, RandomVariable[] realizationPredictor) EuropeanOptionWithBoundary.getBoundaryAdjustment
(double fromTime, double toTime, AssetModelMonteCarloSimulationModel model, RandomVariable continuationValues) -
Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation
Modifier and TypeInterfaceDescriptioninterface
Interface providing additional methods for random variable implementingRandomVariable
allowing automatic differentiation.Modifier and TypeMethodDescriptionAbstractRandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable
(double time, double value) AbstractRandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable
(double time, double[] values) RandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable
(double time, double value) Create a (deterministic) random variable, which is not differentiable, from a constant.RandomVariableDifferentiableFactory.createRandomVariableNonDifferentiable
(double time, double[] values) Create a random variable, which is not differentiable, from an array using a specific filtration time.Modifier and TypeMethodDescriptiondefault Map<Long,
RandomVariable> RandomVariableDifferentiable.getGradient()
Returns the gradient of this random variable with respect to all its leaf nodes.RandomVariableDifferentiable.getGradient
(Set<Long> independentIDs) Returns the gradient of this random variable with respect to the given IDs.default Map<String,
RandomVariable> IndependentModelParameterProvider.getModelParameters()
Returns a map of independent model parameters of this model.default Map<Long,
RandomVariable> RandomVariableDifferentiable.getTangents()
Returns the tangents of this random variable with respect to all its dependent nodes.RandomVariableDifferentiable.getTangents
(Set<Long> dependentIDs) Returns the tangents of this random variable with respect to the given dependent node IDs (if dependent). -
Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation.backward
Modifier and TypeClassDescriptionclass
Implementation ofRandomVariableDifferentiable
using the backward algorithmic differentiation (adjoint algorithmic differentiation, AAD).Modifier and TypeMethodDescriptionRandomVariableDifferentiableAAD.abs()
RandomVariableDifferentiableAAD.accrue
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAAD.add
(double value) RandomVariableDifferentiableAAD.add
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.addProduct
(RandomVariable factor1, double factor2) RandomVariableDifferentiableAAD.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableDifferentiableAAD.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAAD.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableDifferentiableAAD.apply
(DoubleUnaryOperator operator) RandomVariableDifferentiableAAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableDifferentiableAAD.average()
RandomVariableDifferentiableAAD.bus
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.cache()
RandomVariableDifferentiableAAD.cap
(double cap) RandomVariableDifferentiableAAD.cap
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableDifferentiableAAD.cos()
RandomVariableDifferentiableAAD.discount
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAAD.div
(double value) RandomVariableDifferentiableAAD.div
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.exp()
RandomVariableDifferentiableAAD.floor
(double floor) RandomVariableDifferentiableAAD.floor
(RandomVariable floor) RandomVariableDifferentiableAAD.getConditionalExpectation
(ConditionalExpectationEstimator estimator) RandomVariableDifferentiableAAD.getMaxAsRandomVariableAAD()
RandomVariableDifferentiableAAD.getMinAsRandomVariableAAD()
RandomVariableDifferentiableAAD.getSampleVarianceAsRandomVariableAAD()
RandomVariableDifferentiableAAD.getStandardDeviationAsRandomVariableAAD()
RandomVariableDifferentiableAAD.getStandardErrorAsRandomVariableAAD()
RandomVariableDifferentiableAAD.getValues()
Returns the underlying values.RandomVariableDifferentiableAAD.getVarianceAsRandomVariableAAD()
RandomVariableDifferentiableAAD.invert()
RandomVariableDifferentiableAAD.isNaN()
RandomVariableDifferentiableAAD.log()
RandomVariableDifferentiableAAD.mult
(double value) RandomVariableDifferentiableAAD.mult
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.pow
(double exponent) RandomVariableDifferentiableAAD.sin()
RandomVariableDifferentiableAAD.sqrt()
RandomVariableDifferentiableAAD.squared()
RandomVariableDifferentiableAAD.sub
(double value) RandomVariableDifferentiableAAD.sub
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAAD.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionRandomVariableDifferentiableAAD.getGradient
(Set<Long> independentIDs) Returns the gradient of this random variable with respect to all its leaf nodes.RandomVariableDifferentiableAAD.getTangents
(Set<Long> dependentIDs) Modifier and TypeMethodDescriptionRandomVariableDifferentiableAAD.accrue
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAAD.add
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.addProduct
(RandomVariable factor1, double factor2) RandomVariableDifferentiableAAD.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableDifferentiableAAD.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAAD.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableDifferentiableAAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableDifferentiableAAD.bus
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.cap
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableDifferentiableAAD.discount
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAAD.div
(RandomVariable randomVariable) boolean
RandomVariableDifferentiableAAD.equals
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.floor
(RandomVariable floor) double
RandomVariableDifferentiableAAD.getAverage
(RandomVariable probabilities) double
RandomVariableDifferentiableAAD.getQuantile
(double quantile, RandomVariable probabilities) double
RandomVariableDifferentiableAAD.getStandardDeviation
(RandomVariable probabilities) double
RandomVariableDifferentiableAAD.getStandardError
(RandomVariable probabilities) double
RandomVariableDifferentiableAAD.getVariance
(RandomVariable probabilities) RandomVariableDifferentiableAAD.mult
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.of
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.sub
(RandomVariable randomVariable) RandomVariableDifferentiableAAD.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAAD.vid
(RandomVariable randomVariable) ModifierConstructorDescriptionRandomVariableDifferentiableAAD
(RandomVariable randomVariable) RandomVariableDifferentiableAAD
(RandomVariable values, List<net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorTreeNode> argumentOperatorTreeNodes, List<RandomVariable> argumentValues, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority) RandomVariableDifferentiableAAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory) RandomVariableDifferentiableAAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority) RandomVariableDifferentiableAAD
(RandomVariable values, RandomVariableDifferentiableAADFactory factory) ModifierConstructorDescriptionRandomVariableDifferentiableAAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory) RandomVariableDifferentiableAAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD.OperatorType operator, RandomVariableDifferentiableAADFactory factory, int methodArgumentTypePriority) -
Uses of RandomVariable in net.finmath.montecarlo.automaticdifferentiation.forward
Modifier and TypeClassDescriptionclass
Implementation ofRandomVariableDifferentiable
using the forward algorithmic differentiation (AD).Modifier and TypeMethodDescriptionRandomVariableDifferentiableAD.abs()
RandomVariableDifferentiableAD.accrue
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAD.add
(double value) RandomVariableDifferentiableAD.add
(RandomVariable randomVariable) RandomVariableDifferentiableAD.addProduct
(RandomVariable factor1, double factor2) RandomVariableDifferentiableAD.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableDifferentiableAD.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAD.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableDifferentiableAD.apply
(DoubleUnaryOperator operator) RandomVariableDifferentiableAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableDifferentiableAD.average()
RandomVariableDifferentiableAD.bus
(RandomVariable randomVariable) RandomVariableDifferentiableAD.cache()
RandomVariableDifferentiableAD.cap
(double cap) RandomVariableDifferentiableAD.cap
(RandomVariable randomVariable) RandomVariableDifferentiableAD.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableDifferentiableAD.cos()
RandomVariableDifferentiableAD.discount
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAD.div
(double value) RandomVariableDifferentiableAD.div
(RandomVariable randomVariable) RandomVariableDifferentiableAD.exp()
RandomVariableDifferentiableAD.floor
(double floor) RandomVariableDifferentiableAD.floor
(RandomVariable floor) RandomVariableDifferentiableAD.getConditionalExpectation
(ConditionalExpectationEstimator estimator) RandomVariableDifferentiableAD.getMaxAsRandomVariableAAD()
RandomVariableDifferentiableAD.getMinAsRandomVariableAAD()
RandomVariableDifferentiableAD.getSampleVarianceAsRandomVariableAAD()
RandomVariableDifferentiableAD.getStandardDeviationAsRandomVariableAAD()
RandomVariableDifferentiableAD.getStandardErrorAsRandomVariableAAD()
RandomVariableDifferentiableAD.getValues()
Returns the underlying values.RandomVariableDifferentiableAD.getVarianceAsRandomVariableAAD()
RandomVariableDifferentiableAD.invert()
RandomVariableDifferentiableAD.isNaN()
RandomVariableDifferentiableAD.log()
RandomVariableDifferentiableAD.mult
(double value) RandomVariableDifferentiableAD.mult
(RandomVariable randomVariable) RandomVariableDifferentiableAD.pow
(double exponent) RandomVariableDifferentiableAD.sin()
RandomVariableDifferentiableAD.sqrt()
RandomVariableDifferentiableAD.squared()
RandomVariableDifferentiableAD.sub
(double value) RandomVariableDifferentiableAD.sub
(RandomVariable randomVariable) RandomVariableDifferentiableAD.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAD.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionRandomVariableDifferentiableAD.getGradient
(Set<Long> independentIDs) Returns the gradient of this random variable with respect to all its leaf nodes.RandomVariableDifferentiableAD.getTangents()
RandomVariableDifferentiableAD.getTangents
(Set<Long> dependentIDs) Modifier and TypeMethodDescriptionRandomVariableDifferentiableAD.accrue
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAD.add
(RandomVariable randomVariable) RandomVariableDifferentiableAD.addProduct
(RandomVariable factor1, double factor2) RandomVariableDifferentiableAD.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariableDifferentiableAD.addRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAD.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableDifferentiableAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableDifferentiableAD.bus
(RandomVariable randomVariable) RandomVariableDifferentiableAD.cap
(RandomVariable randomVariable) RandomVariableDifferentiableAD.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariableDifferentiableAD.discount
(RandomVariable rate, double periodLength) RandomVariableDifferentiableAD.div
(RandomVariable randomVariable) boolean
RandomVariableDifferentiableAD.equals
(RandomVariable randomVariable) RandomVariableDifferentiableAD.floor
(RandomVariable floor) double
RandomVariableDifferentiableAD.getAverage
(RandomVariable probabilities) double
RandomVariableDifferentiableAD.getQuantile
(double quantile, RandomVariable probabilities) double
RandomVariableDifferentiableAD.getStandardDeviation
(RandomVariable probabilities) double
RandomVariableDifferentiableAD.getStandardError
(RandomVariable probabilities) double
RandomVariableDifferentiableAD.getVariance
(RandomVariable probabilities) RandomVariableDifferentiableAD.mult
(RandomVariable randomVariable) RandomVariableDifferentiableAD.of
(RandomVariable randomVariable) RandomVariableDifferentiableAD.sub
(RandomVariable randomVariable) RandomVariableDifferentiableAD.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableDifferentiableAD.vid
(RandomVariable randomVariable) ModifierConstructorDescriptionRandomVariableDifferentiableAD
(RandomVariable randomVariable) RandomVariableDifferentiableAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator) RandomVariableDifferentiableAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator, int methodArgumentTypePriority) ModifierConstructorDescriptionRandomVariableDifferentiableAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator) RandomVariableDifferentiableAD
(RandomVariable values, List<RandomVariable> arguments, ConditionalExpectationEstimator estimator, net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD.OperatorType operator, int methodArgumentTypePriority) -
Uses of RandomVariable in net.finmath.montecarlo.conditionalexpectation
Modifier and TypeMethodDescriptionMonteCarloConditionalExpectationRegression.RegressionBasisFunctions.getBasisFunctions()
MonteCarloConditionalExpectationRegression.RegressionBasisFunctionsGiven.getBasisFunctions()
RegressionBasisFunctionsFromProducts.getBasisFunctions
(double evaluationTime, MonteCarloSimulationModel model) RegressionBasisFunctionsProvider.getBasisFunctions
(double evaluationTime, MonteCarloSimulationModel model) Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.MonteCarloConditionalExpectationRegression.getConditionalExpectation
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionMonteCarloConditionalExpectationRegression.getConditionalExpectation
(RandomVariable randomVariable) MonteCarloConditionalExpectationLinearRegressionFactory.getConditionalExpectationEstimator
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor) MonteCarloConditionalExpectationLocalizedOnDependentRegressionFactory.getConditionalExpectationEstimator
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor) MonteCarloConditionalExpectationRegressionFactory.getConditionalExpectationEstimator
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor) Creates an object implementing aConditionalExpectationEstimator
for conditional expectation estimation.double[]
MonteCarloConditionalExpectationRegression.getLinearRegressionParameters
(RandomVariable dependents) Return the solution x of XTX x = XT y for a given y.double[]
MonteCarloConditionalExpectationRegressionLocalizedOnDependents.getLinearRegressionParameters
(RandomVariable dependents) Return the solution x of XTX x = XT y for a given y.double[]
LinearRegression.getRegressionCoefficients
(RandomVariable value) Get the vector of regression coefficients.ModifierConstructorDescriptionLinearRegression
(RandomVariable[] basisFunctions) Create the linear regression with a set of basis functions.MonteCarloConditionalExpectationRegression
(RandomVariable[] basisFunctions) Creates a class for conditional expectation estimation.MonteCarloConditionalExpectationRegression
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor) Creates a class for conditional expectation estimation.Creates a class for conditional expectation estimation.MonteCarloConditionalExpectationRegressionLocalizedOnDependents
(RandomVariable[] basisFunctionsEstimator, double standardDeviations) Creates a class for conditional expectation estimation.MonteCarloConditionalExpectationRegressionLocalizedOnDependents
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor) Creates a class for conditional expectation estimation.MonteCarloConditionalExpectationRegressionLocalizedOnDependents
(RandomVariable[] basisFunctionsEstimator, RandomVariable[] basisFunctionsPredictor, double standardDeviations) Creates a class for conditional expectation estimation.RegressionBasisFunctionsGiven
(RandomVariable[] basisFunctions) -
Uses of RandomVariable in net.finmath.montecarlo.crosscurrency
Modifier and TypeMethodDescriptionCrossCurrencyTermStructureMonteCarloSimulationModel.getExchangeRate
(String fromCurve, String toCurve, double time) Return the (cross curve or currency) exchange rate for a given simulation time.CrossCurrencyTermStructureMonteCarloSimulationModel.getForwardRate
(String curve, double time, double periodStart, double periodEnd) Return the forward rate for a given simulation time and a given period start and period end.CrossCurrencyTermStructureMonteCarloSimulationModel.getNumeraire
(double time) Return the numeraire at a given time. -
Uses of RandomVariable in net.finmath.montecarlo.hybridassetinterestrate
Modifier and TypeMethodDescriptionHybridAssetLIBORModelMonteCarloSimulationFromModels.getAssetValue
(double time, int assetIndex) HybridAssetLIBORModelMonteCarloSimulationFromModels.getAssetValue
(int timeIndex, int assetIndex) ConvexityAdjustedModel.getDrift
(RandomVariable[] driftUnadjusted, MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HybridAssetLIBORModelMonteCarloSimulationFromModels.getForwardRate
(double time, double periodStart, double periodEnd) HybridAssetLIBORModelMonteCarloSimulationFromModels.getLIBOR
(int timeIndex, int liborIndex) HybridAssetLIBORModelMonteCarloSimulationFromModels.getLIBORs
(int timeIndex) CrossCurrencyLIBORMarketModelFromModels.getMonteCarloWeights
(double time) CrossCurrencyLIBORMarketModelFromModels.getMonteCarloWeights
(int timeIndex) HybridAssetLIBORModelMonteCarloSimulationFromModels.getMonteCarloWeights
(double time) HybridAssetLIBORModelMonteCarloSimulationFromModels.getMonteCarloWeights
(int timeIndex) CrossCurrencyLIBORMarketModelFromModels.getNumeraire
(double time) CrossCurrencyLIBORMarketModelFromModels.getNumeraire
(String account, double time) HybridAssetLIBORModelMonteCarloSimulationFromModels.getNumeraire
(double time) HybridAssetLIBORModelMonteCarloSimulationFromModels.getNumeraire
(int timeIndex) HybridAssetMonteCarloSimulation.getNumeraire
(double time) Return the (default) numeraire at a given time.HybridAssetMonteCarloSimulation.getNumeraire
(String account, double time) Return the numeraire associated with a given (collateral or funding) account at a given time.CrossCurrencyLIBORMarketModelFromModels.getRandomVariableForConstant
(double value) HybridAssetLIBORModelMonteCarloSimulationFromModels.getRandomVariableForConstant
(double value) CrossCurrencyLIBORMarketModelFromModels.getValue
(RiskFactorID riskFactorIdentifyer, double time) HybridAssetMonteCarloSimulation.getValue
(RiskFactorID riskFactorIdentifyer, double time) Return the random variable of a risk factor with a given name at a given observation time index.Modifier and TypeMethodDescriptionHybridAssetLIBORModelMonteCarloSimulationFromModels.getModelParameters()
Modifier and TypeMethodDescriptionConvexityAdjustedModel.getDrift
(RandomVariable[] driftUnadjusted, MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) -
Uses of RandomVariable in net.finmath.montecarlo.hybridassetinterestrate.products
Modifier and TypeMethodDescriptionBond.getValue
(double evaluationTime, HybridAssetMonteCarloSimulation model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.BondWithForeignNumeraire.getValue
(double evaluationTime, HybridAssetMonteCarloSimulation model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ForwardRateAgreementGeneralized.getValue
(double evaluationTime, HybridAssetMonteCarloSimulation model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.abstract RandomVariable
HybridAssetMonteCarloProduct.getValue
(double evaluationTime, HybridAssetMonteCarloSimulation model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.HybridAssetMonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) HybridAssetMonteCarloProduct.getValueForModifiedData
(double evaluationTime, MonteCarloSimulationModel monteCarloSimulationInterface, Map<String, Object> dataModified) ModifierConstructorDescriptionForwardRateAgreementGeneralized
(LocalDateTime referenceDate, String currency, double fixing, double periodStart, double periodEnd, RandomVariable spread, RandomVariable cap, RandomVariable floor) -
Uses of RandomVariable in net.finmath.montecarlo.interestrate
Modifier and TypeMethodDescriptiondefault RandomVariable
TermStructureModel.getForwardDiscountBond
(MonteCarloProcess process, double time, double maturity) Returns the time \( t \) forward bond derived from the numeraire, i.e., \( P(T;t) = E( \frac{N(t)}{N(T)} \vert \mathcal{F}_{t} ) \).LIBORMonteCarloSimulationFromLIBORModel.getForwardRate
(double time, double periodStart, double periodEnd) LIBORMonteCarloSimulationFromTermStructureModel.getForwardRate
(double time, double periodStart, double periodEnd) TermStructureModel.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) Returns the time \( t \) forward rate on the models forward curve.TermStructureMonteCarloSimulationFromTermStructureModel.getForwardRate
(double time, double periodStart, double periodEnd) TermStructureMonteCarloSimulationModel.getForwardRate
(double time, double periodStart, double periodEnd) Return the forward rate for a given simulation time and a given period start and period end.default RandomVariable
TermStructureMonteCarloSimulationModel.getForwardRate
(LocalDateTime date, LocalDateTime periodStartDate, LocalDateTime periodEndDate) Return the forward rate for a given simulation time and a given period start and period end.LIBORModel.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) Return the forward rate at a given timeIndex and for a given liborIndex.LIBORModelMonteCarloSimulationModel.getLIBOR
(int timeIndex, int liborIndex) Return the forward rate for a given simulation time index and a given forward rate index.LIBORMonteCarloSimulationFromLIBORModel.getLIBOR
(int timeIndex, int liborIndex) LIBORMonteCarloSimulationFromTermStructureModel.getLIBOR
(int timeIndex, int liborIndex) default RandomVariable
TermStructureModel.getLIBOR
(MonteCarloProcess process, double time, double periodStart, double periodEnd) Returns the time \( t \) forward rate on the models forward curve.default RandomVariable
TermStructureMonteCarloSimulationModel.getLIBOR
(double time, double periodStart, double periodEnd) Return the forward rate for a given simulation time and a given period start and period end.default RandomVariable
TermStructureMonteCarloSimulationModel.getLIBOR
(LocalDateTime date, LocalDateTime periodStartDate, LocalDateTime periodEndDate) Return the forward rate for a given simulation time and a given period start and period end.LIBORModelMonteCarloSimulationModel.getLIBORs
(int timeIndex) Return the forward rate curve for a given simulation time index.LIBORMonteCarloSimulationFromLIBORModel.getLIBORs
(int timeIndex) LIBORMonteCarloSimulationFromTermStructureModel.getLIBORs
(int timeIndex) LIBORMonteCarloSimulationFromLIBORModel.getMonteCarloWeights
(double time) LIBORMonteCarloSimulationFromLIBORModel.getMonteCarloWeights
(int timeIndex) LIBORMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights
(double time) LIBORMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights
(int timeIndex) TermStructureMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights
(double time) TermStructureMonteCarloSimulationFromTermStructureModel.getMonteCarloWeights
(int timeIndex) LIBORMonteCarloSimulationFromLIBORModel.getNumeraire
(double time) LIBORMonteCarloSimulationFromTermStructureModel.getNumeraire
(double time) TermStructureMonteCarloSimulationFromTermStructureModel.getNumeraire
(double time) TermStructureMonteCarloSimulationModel.getNumeraire
(double time) Return the numeraire at a given time.default RandomVariable
TermStructureMonteCarloSimulationModel.getNumeraire
(LocalDateTime date) Return the numeraire at a given time.LIBORMonteCarloSimulationFromLIBORModel.getRandomVariableForConstant
(double value) LIBORMonteCarloSimulationFromTermStructureModel.getRandomVariableForConstant
(double value) TermStructureMonteCarloSimulationFromTermStructureModel.getRandomVariableForConstant
(double value) CalibrationProduct.getTargetValue()
Modifier and TypeMethodDescriptionLIBORMonteCarloSimulationFromLIBORModel.getModelParameters()
LIBORMonteCarloSimulationFromTermStructureModel.getModelParameters()
TermStructureMonteCarloSimulationFromTermStructureModel.getModelParameters()
ModifierConstructorDescriptionCalibrationProduct
(String name, AbstractTermStructureMonteCarloProduct product, RandomVariable targetValue, double weight) CalibrationProduct
(String name, AbstractTermStructureMonteCarloProduct product, RandomVariable targetValue, double weight, int priority) Construct a calibration product.CalibrationProduct
(AbstractTermStructureMonteCarloProduct product, RandomVariable targetValue, double weight) -
Uses of RandomVariable in net.finmath.montecarlo.interestrate.models
Modifier and TypeMethodDescriptionHullWhiteModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithConstantCoeff.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithDirectSimulation.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithShiftExtension.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelFromCovarianceModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelStandard.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelWithTenorRefinement.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithConstantCoeff.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithDirectSimulation.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithShiftExtension.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelFromCovarianceModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelStandard.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelWithTenorRefinement.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithConstantCoeff.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithDirectSimulation.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithShiftExtension.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) LIBORMarketModelFromCovarianceModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.LIBORMarketModelStandard.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.LIBORMarketModelWithTenorRefinement.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.protected RandomVariable
LIBORMarketModelStandard.getDriftEuler
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] liborVectorStart) HullWhiteModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithConstantCoeff.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithDirectSimulation.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithShiftExtension.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelFromCovarianceModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelStandard.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelWithTenorRefinement.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModel.getForwardDiscountBond
(MonteCarloProcess process, double time, double maturity) LIBORMarketModelFromCovarianceModel.getForwardDiscountBond
(MonteCarloProcess process, double time, double maturity) HullWhiteModel.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) HullWhiteModelWithConstantCoeff.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) HullWhiteModelWithDirectSimulation.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) HullWhiteModelWithShiftExtension.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) LIBORMarketModelFromCovarianceModel.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) LIBORMarketModelStandard.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) LIBORMarketModelWithTenorRefinement.getForwardRate
(MonteCarloProcess process, double time, double periodStart, double periodEnd) HullWhiteModel.getInitialState
(MonteCarloProcess process) HullWhiteModelWithConstantCoeff.getInitialState
(MonteCarloProcess process) HullWhiteModelWithDirectSimulation.getInitialState
(MonteCarloProcess process) HullWhiteModelWithShiftExtension.getInitialState
(MonteCarloProcess process) LIBORMarketModelFromCovarianceModel.getInitialState
(MonteCarloProcess process) LIBORMarketModelStandard.getInitialState
(MonteCarloProcess process) LIBORMarketModelWithTenorRefinement.getInitialState
(MonteCarloProcess process) HullWhiteModel.getIntegratedBondSquaredVolatility
(double time, double maturity) HullWhiteModel.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) HullWhiteModelWithConstantCoeff.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) HullWhiteModelWithDirectSimulation.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) HullWhiteModelWithShiftExtension.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) LIBORMarketModelFromCovarianceModel.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) LIBORMarketModelStandard.getLIBOR
(MonteCarloProcess process, int timeIndex, int liborIndex) LIBORMarketModelWithTenorRefinement.getLIBOR
(MonteCarloProcess process, int timeIndex, double periodStart, double periodEnd) LIBORMarketModelWithTenorRefinement.getLIBORForStateVariable
(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd) HullWhiteModel.getNumeraire
(MonteCarloProcess process, double time) HullWhiteModelWithConstantCoeff.getNumeraire
(MonteCarloProcess process, double time) HullWhiteModelWithDirectSimulation.getNumeraire
(MonteCarloProcess process, double time) HullWhiteModelWithShiftExtension.getNumeraire
(MonteCarloProcess process, double time) LIBORMarketModelFromCovarianceModel.getNumeraire
(MonteCarloProcess process, double time) Return the numeraire at a given time.LIBORMarketModelStandard.getNumeraire
(MonteCarloProcess process, double time) Return the numeraire at a given time.LIBORMarketModelWithTenorRefinement.getNumeraire
(MonteCarloProcess process, double time) Return the numeraire at a given time.protected RandomVariable
LIBORMarketModelFromCovarianceModel.getNumerairetUnAdjusted
(MonteCarloProcess process, double time) HullWhiteModel.getRandomVariableForConstant
(double value) HullWhiteModelWithConstantCoeff.getRandomVariableForConstant
(double value) HullWhiteModelWithDirectSimulation.getRandomVariableForConstant
(double value) HullWhiteModelWithShiftExtension.getRandomVariableForConstant
(double value) LIBORMarketModelFromCovarianceModel.getRandomVariableForConstant
(double value) LIBORMarketModelStandard.getRandomVariableForConstant
(double value) LIBORMarketModelWithTenorRefinement.getRandomVariableForConstant
(double value) HullWhiteModel.getShortRateConditionalVariance
(double time, double maturity) Calculates the variance \( \mathop{Var}(r(t) \vert r(s) ) \), that is \( \int_{s}^{t} \sigma^{2}(\tau) \exp(-2 \cdot \int_{\tau}^{t} a(u) \mathrm{d}u ) \ \mathrm{d}\tau \) where \( a \) is the meanReversion and \( \sigma \) is the short rate instantaneous volatility.LIBORMarketModelWithTenorRefinement.getStateVariable
(MonteCarloProcess process, int timeIndex, double periodStart, double periodEnd) LIBORMarketModelWithTenorRefinement.getStateVariableForPeriod
(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd) Modifier and TypeMethodDescriptionHullWhiteModel.getModelParameters()
HullWhiteModelWithConstantCoeff.getModelParameters()
HullWhiteModelWithDirectSimulation.getModelParameters()
HullWhiteModelWithShiftExtension.getModelParameters()
LIBORMarketModelFromCovarianceModel.getModelParameters()
LIBORMarketModelStandard.getModelParameters()
LIBORMarketModelFromCovarianceModel.getNumeraireAdjustments()
Modifier and TypeMethodDescriptionHullWhiteModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithConstantCoeff.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithDirectSimulation.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithShiftExtension.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelFromCovarianceModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelStandard.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelWithTenorRefinement.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithConstantCoeff.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithDirectSimulation.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModelWithShiftExtension.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelFromCovarianceModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelStandard.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) LIBORMarketModelWithTenorRefinement.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) HullWhiteModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithConstantCoeff.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithDirectSimulation.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) HullWhiteModelWithShiftExtension.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) LIBORMarketModelFromCovarianceModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.LIBORMarketModelStandard.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.LIBORMarketModelWithTenorRefinement.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Return the complete vector of the drift for the time index timeIndex, given that current state is realizationAtTimeIndex.protected RandomVariable
LIBORMarketModelStandard.getDriftEuler
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] liborVectorStart) HullWhiteModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithConstantCoeff.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithDirectSimulation.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) HullWhiteModelWithShiftExtension.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelFromCovarianceModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelStandard.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelWithTenorRefinement.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) LIBORMarketModelWithTenorRefinement.getLIBORForStateVariable
(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd) LIBORMarketModelWithTenorRefinement.getStateVariableForPeriod
(TimeDiscretization liborPeriodDiscretization, RandomVariable[] stateVariables, double periodStart, double periodEnd) -
Uses of RandomVariable in net.finmath.montecarlo.interestrate.models.covariance
Modifier and TypeMethodDescriptionAbstractLIBORCovarianceModel.getCovariance
(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex) AbstractLIBORCovarianceModel.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getCovariance
(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex) Returns the instantaneous covariance calculated from factor loadings.LIBORCovarianceModel.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) Returns the instantaneous covariance calculated from factor loadings.LIBORCovarianceModelFromVolatilityAndCorrelation.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) DisplacedLocalVolatilityModel.getDisplacement()
ExponentialDecayLocalVolatilityModel.getDisplacement()
AbstractLIBORCovarianceModel.getFactorLoading
(double time, double component, RandomVariable[] realizationAtTimeIndex) AbstractLIBORCovarianceModel.getFactorLoading
(double time, int component, RandomVariable[] realizationAtTimeIndex) abstract RandomVariable[]
AbstractLIBORCovarianceModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlendedLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) DisplacedLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) ExponentialDecayLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) HullWhiteLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getFactorLoading
(double time, double component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time and a given component.LIBORCovarianceModel.getFactorLoading
(double time, int component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time and component index.LIBORCovarianceModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time index and component index.LIBORCovarianceModelBH.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm5Param.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm7Param.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticHestonVolatility.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticVolatility.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) TermStructCovarianceModelFromLIBORCovarianceModel.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) TermStructCovarianceModelFromLIBORCovarianceModelParametric.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) TermStructureFactorLoadingsModel.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) Return the factor loading for a given time and a term structure period.abstract RandomVariable
AbstractLIBORCovarianceModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) BlendedLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) DisplacedLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) ExponentialDecayLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) HullWhiteLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) Returns the pseudo inverse of the factor matrix.LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticHestonVolatility.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticVolatility.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) ShortRateVolatilityModel.getMeanReversion
(int timeIndex) Returns the value of \( a(t) \) for \( t_{i} \leq t < t_{i+1} \).ShortRateVolatilityModelAsGiven.getMeanReversion
(int timeIndex) ShortRateVolatilityModelHoLee.getMeanReversion
(int timeIndex) ShortRateVolatilityModelPiecewiseConstant.getMeanReversion
(int timeIndex) AbstractLIBORCovarianceModelParametric.getParameter()
Get the parameters of determining this parametric covariance model.abstract RandomVariable[]
AbstractShortRateVolatilityModelParametric.getParameter()
Get the parameters of determining this parametric volatility model.BlendedLocalVolatilityModel.getParameter()
DisplacedLocalVolatilityModel.getParameter()
ExponentialDecayLocalVolatilityModel.getParameter()
abstract RandomVariable[]
LIBORCorrelationModel.getParameter()
LIBORCorrelationModelExponentialDecay.getParameter()
LIBORCorrelationModelThreeParameterExponentialDecay.getParameter()
LIBORCovarianceModelExponentialForm5Param.getParameter()
LIBORCovarianceModelFromVolatilityAndCorrelation.getParameter()
LIBORCovarianceModelStochasticHestonVolatility.getParameter()
LIBORCovarianceModelStochasticVolatility.getParameter()
abstract RandomVariable[]
LIBORVolatilityModel.getParameter()
LIBORVolatilityModelFourParameterExponentialForm.getParameter()
LIBORVolatilityModelFourParameterExponentialFormIntegrated.getParameter()
LIBORVolatilityModelFromGivenMatrix.getParameter()
LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getParameter()
LIBORVolatilityModelPiecewiseConstant.getParameter()
LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getParameter()
LIBORVolatilityModelTwoParameterExponentialForm.getParameter()
ShortRateVolatilityModelParametric.getParameter()
Get the parameters of determining this parametric volatility model.ShortRateVolatilityModelPiecewiseConstant.getParameter()
abstract RandomVariable
LIBORVolatilityModel.getVolatility
(int timeIndex, int component) Implement this method to complete the implementation.LIBORVolatilityModelFourParameterExponentialForm.getVolatility
(int timeIndex, int liborIndex) LIBORVolatilityModelFourParameterExponentialFormIntegrated.getVolatility
(int timeIndex, int liborIndex) LIBORVolatilityModelFromGivenMatrix.getVolatility
(int timeIndex, int component) LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getVolatility
(int timeIndex, int liborIndex) LIBORVolatilityModelPiecewiseConstant.getVolatility
(int timeIndex, int liborIndex) LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getVolatility
(int timeIndex, int liborIndex) LIBORVolatilityModelTwoParameterExponentialForm.getVolatility
(int timeIndex, int liborIndex) ShortRateVolatilityModel.getVolatility
(int timeIndex) Returns the value of \( \sigma(t) \) for \( t_{i} \leq t < t_{i+1} \).ShortRateVolatilityModelAsGiven.getVolatility
(int timeIndex) ShortRateVolatilityModelHoLee.getVolatility
(int timeIndex) ShortRateVolatilityModelPiecewiseConstant.getVolatility
(double time) ShortRateVolatilityModelPiecewiseConstant.getVolatility
(int timeIndex) Modifier and TypeMethodDescriptionabstract LIBORCorrelationModel
LIBORCorrelationModel.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORCorrelationModelExponentialDecay.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORCorrelationModelThreeParameterExponentialDecay.getCloneWithModifiedParameter
(RandomVariable[] parameter) abstract LIBORVolatilityModel
LIBORVolatilityModel.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelFourParameterExponentialForm.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelFourParameterExponentialFormIntegrated.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelFromGivenMatrix.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelMaturityDependentFourParameterExponentialForm.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelPiecewiseConstant.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelTimeHomogenousPiecewiseConstant.getCloneWithModifiedParameter
(RandomVariable[] parameter) LIBORVolatilityModelTwoParameterExponentialForm.getCloneWithModifiedParameter
(RandomVariable[] parameter) AbstractLIBORCovarianceModelParametric.getCloneWithModifiedParameters
(RandomVariable[] parameters) Return an instance of this model using a new set of parameters.AbstractShortRateVolatilityModelParametric.getCloneWithModifiedParameters
(RandomVariable[] parameters) Return an instance of this model using a new set of parameters.BlendedLocalVolatilityModel.getCloneWithModifiedParameters
(RandomVariable[] parameters) DisplacedLocalVolatilityModel.getCloneWithModifiedParameters
(RandomVariable[] parameters) ExponentialDecayLocalVolatilityModel.getCloneWithModifiedParameters
(RandomVariable[] parameters) LIBORCovarianceModelExponentialForm5Param.getCloneWithModifiedParameters
(RandomVariable[] parameters) LIBORCovarianceModelFromVolatilityAndCorrelation.getCloneWithModifiedParameters
(RandomVariable[] parameters) LIBORCovarianceModelStochasticHestonVolatility.getCloneWithModifiedParameters
(RandomVariable[] parameters) LIBORCovarianceModelStochasticVolatility.getCloneWithModifiedParameters
(RandomVariable[] parameters) ShortRateVolatilityModelParametric.getCloneWithModifiedParameters
(RandomVariable[] parameters) Return an instance of this model using a new set of parameters.ShortRateVolatilityModelPiecewiseConstant.getCloneWithModifiedParameters
(RandomVariable[] parameters) AbstractLIBORCovarianceModel.getCovariance
(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex) AbstractLIBORCovarianceModel.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getCovariance
(double time, int component1, int component2, RandomVariable[] realizationAtTimeIndex) Returns the instantaneous covariance calculated from factor loadings.LIBORCovarianceModel.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) Returns the instantaneous covariance calculated from factor loadings.LIBORCovarianceModelFromVolatilityAndCorrelation.getCovariance
(int timeIndex, int component1, int component2, RandomVariable[] realizationAtTimeIndex) AbstractLIBORCovarianceModel.getFactorLoading
(double time, double component, RandomVariable[] realizationAtTimeIndex) AbstractLIBORCovarianceModel.getFactorLoading
(double time, int component, RandomVariable[] realizationAtTimeIndex) abstract RandomVariable[]
AbstractLIBORCovarianceModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) BlendedLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) DisplacedLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) ExponentialDecayLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) HullWhiteLocalVolatilityModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getFactorLoading
(double time, double component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time and a given component.LIBORCovarianceModel.getFactorLoading
(double time, int component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time and component index.LIBORCovarianceModel.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) Return the factor loading for a given time index and component index.LIBORCovarianceModelBH.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm5Param.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm7Param.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticHestonVolatility.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticVolatility.getFactorLoading
(int timeIndex, int component, RandomVariable[] realizationAtTimeIndex) TermStructCovarianceModelFromLIBORCovarianceModel.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) TermStructCovarianceModelFromLIBORCovarianceModelParametric.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) TermStructureFactorLoadingsModel.getFactorLoading
(double time, double periodStart, double periodEnd, TimeDiscretization periodDiscretization, RandomVariable[] realizationAtTimeIndex, TermStructureModel model) Return the factor loading for a given time and a term structure period.abstract RandomVariable
AbstractLIBORCovarianceModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) BlendedLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) DisplacedLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) ExponentialDecayLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) HullWhiteLocalVolatilityModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModel.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) Returns the pseudo inverse of the factor matrix.LIBORCovarianceModelBH.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm5Param.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelExponentialForm7Param.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelFromVolatilityAndCorrelation.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticHestonVolatility.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) LIBORCovarianceModelStochasticVolatility.getFactorLoadingPseudoInverse
(int timeIndex, int component, int factor, RandomVariable[] realizationAtTimeIndex) ModifierConstructorDescriptionBlendedLocalVolatilityModel
(AbstractLIBORCovarianceModelParametric covarianceModel, ForwardCurve forwardCurve, RandomVariable displacement, boolean isCalibrateable) Displaced diffusion model build on top of a standard covariance model.DisplacedLocalVolatilityModel
(AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable displacement, boolean isCalibrateable) Displaced model build on top of a standard covariance model.ExponentialDecayLocalVolatilityModel
(RandomVariableFactory randomVariableFactory, AbstractLIBORCovarianceModelParametric covarianceModel, RandomVariable decay, boolean isCalibrateable) Exponential decay model build on top of a standard covariance model.LIBORCovarianceModelExponentialForm5Param
(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, int numberOfFactors, RandomVariable[] parameters) LIBORCovarianceModelStochasticHestonVolatility
(AbstractLIBORCovarianceModelParametric covarianceModel, BrownianMotion brownianMotion, RandomVariable kappa, RandomVariable theta, RandomVariable xi, boolean isCalibrateable) Create a modification of a givenAbstractLIBORCovarianceModelParametric
with a stochastic volatility scaling.LIBORCovarianceModelStochasticVolatility
(AbstractLIBORCovarianceModelParametric covarianceModel, BrownianMotion brownianMotion, RandomVariable nu, RandomVariable rho, boolean isCalibrateable) Create a modification of a givenAbstractLIBORCovarianceModelParametric
with a stochastic volatility scaling.LIBORVolatilityModelFourParameterExponentialForm
(RandomVariableFactory randomVariableFactory, 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)) + dLIBORVolatilityModelFourParameterExponentialForm
(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)) + dLIBORVolatilityModelFourParameterExponentialFormIntegrated
(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, RandomVariable c, RandomVariable 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 randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility, boolean isCalibrateable) Creates a simple volatility model using given piece-wise constant values on a given discretization grid.LIBORVolatilityModelFromGivenMatrix
(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[][] volatility) Creates a simple volatility model using given piece-wise constant values on a given discretization grid.LIBORVolatilityModelFromGivenMatrix
(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
(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable[] parameterA, RandomVariable[] parameterB, RandomVariable[] parameterC, RandomVariable[] parameterD) LIBORVolatilityModelPiecewiseConstant
(TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, TimeDiscretization simulationTimeDiscretization, TimeDiscretization timeToMaturityDiscretization, RandomVariable[] volatility, boolean isCalibrateable) LIBORVolatilityModelTimeHomogenousPiecewiseConstant
(RandomVariableFactory randomVariableFactory, 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.LIBORVolatilityModelTimeHomogenousPiecewiseConstant
(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 randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization liborPeriodDiscretization, RandomVariable a, RandomVariable b, boolean isCalibrateable) Creates the volatility model σi(tj) = a * exp(-b (Ti-tj))ShortRateVolatilityModelPiecewiseConstant
(RandomVariableFactory randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable) ShortRateVolatilityModelPiecewiseConstant
(RandomVariableFactory randomVariableFactory, TimeDiscretization timeDiscretization, TimeDiscretization volatilityTimeDiscretization, RandomVariable[] volatility, RandomVariable[] meanReversion, boolean isVolatilityCalibrateable, boolean isMeanReversionCalibrateable) -
Uses of RandomVariable in net.finmath.montecarlo.interestrate.products
Modifier and TypeMethodDescriptionBermudanSwaption.getBasisFunctions
(double fixingDate, LIBORModelMonteCarloSimulationModel model) Return the basis functions for the regression suitable for this product.BermudanSwaption.getBasisFunctions
(double fixingDate, MonteCarloSimulationModel model) Return the basis functions for the regression suitable for this product.BermudanSwaptionFromSwapSchedules.getBasisFunctions
(double evaluationTime, LIBORModelMonteCarloSimulationModel model) Provides a set of \( \mathcal{F}_{t} \)-measurable random variables which can serve as regression basis functions.BermudanSwaptionFromSwapSchedules.getBasisFunctions
(double evaluationTime, MonteCarloSimulationModel model) Swaption.getExerciseIndicator
(LIBORModelMonteCarloSimulationModel model) Deprecated.SwaptionATM.getImpliedBachelierATMOptionVolatility
(RandomVariable optionValue, double optionMaturity, double swapAnnuity) Calculates ATM Bachelier implied volatilities.abstract RandomVariable
AbstractLIBORMonteCarloProduct.getValue
(double evaluationTime, LIBORModelMonteCarloSimulationModel model) AbstractLIBORMonteCarloProduct.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) abstract RandomVariable
AbstractTermStructureMonteCarloProduct.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) AbstractTermStructureMonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) BermudanSwaption.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.BermudanSwaptionFromSwapSchedules.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) Bond.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.CancelableSwap.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Caplet.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.CMSOption.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.DigitalCaplet.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.DigitalFloorlet.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.FlexiCap.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ForwardRateVolatilitySurfaceCurvature.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) LIBORBond.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.MoneyMarketAccount.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) Portfolio.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SimpleCappedFlooredFloatingRateBond.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SimpleSwap.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SimpleZeroSwap.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Swap.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwapLeg.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwapLegWithFundingProvider.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaprateCovarianceAnalyticApproximation.getValue
(double evaluationTime, MonteCarloSimulationModel model) Swaption.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SwaptionAnalyticApproximation.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionAnalyticApproximationRebonato.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionATM.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionFromSwapSchedules.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionGeneralizedAnalyticApproximation.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionSimple.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SwaptionSingleCurve.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SwaptionSingleCurveAnalyticApproximation.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) SwaptionWithComponents.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.SwapWithComponents.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.TermStructureMonteCarloProduct.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.AbstractTermStructureMonteCarloProduct.getValueForModifiedData
(double evaluationTime, MonteCarloSimulationModel monteCarloSimulationModel, Map<String, Object> dataModified) static RandomVariable
SwaptionFromSwapSchedules.getValueOfLegAnalytic
(double evaluationTime, TermStructureMonteCarloSimulationModel model, Schedule schedule, boolean paysFloatingRate, double fixRate, double notional) Determines the time \( t \)-measurable value of a swap leg (can handle fix or float).ForwardRateVolatilitySurfaceCurvature.getValues
(double evaluationTime, LIBORMarketModel model) Calculates the squared curvature of the LIBOR instantaneous variance.SwaprateCovarianceAnalyticApproximation.getValues
(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model) Calculates the approximated integrated instantaneous covariance of two swap rates, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).SwaptionAnalyticApproximation.getValues
(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model) Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).SwaptionAnalyticApproximationRebonato.getValues
(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model) Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).SwaptionGeneralizedAnalyticApproximation.getValues
(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model) Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d S/d L (t) = d S/d L (0).SwaptionSingleCurveAnalyticApproximation.getValues
(double evaluationTime, TimeDiscretization timeDiscretization, LIBORMarketModel model) Calculates the approximated integrated instantaneous variance of the swap rate, using the approximation d log(S(t))/d log(L(t)) = d log(S(0))/d log(L(0)).Modifier and TypeMethodDescriptiondouble[]
BermudanSwaptionFromSwapSchedules.getExerciseProbabilitiesFromTimes
(LocalDateTime localDateTime, RandomVariable exerciseTimes) Determines the vector of exercise probabilities for a givenRandomVariable
of exerciseTimes.SwaptionATM.getImpliedBachelierATMOptionVolatility
(RandomVariable optionValue, double optionMaturity, double swapAnnuity) Calculates ATM Bachelier implied volatilities. -
Uses of RandomVariable in net.finmath.montecarlo.interestrate.products.components
Modifier and TypeMethodDescriptionOption.getBasisFunctions
(double exerciseDate, LIBORModelMonteCarloSimulationModel model) Return the regression basis functions.Option.getBasisFunctions
(double evaluationTime, MonteCarloSimulationModel model) abstract RandomVariable
AbstractPeriod.getCoupon
(double evaluationTime, TermStructureMonteCarloSimulationModel model) Period.getCoupon
(double evaluationTime, TermStructureMonteCarloSimulationModel model) AccruingNotional.getNotionalAtPeriodEnd
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) Notional.getNotionalAtPeriodEnd
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) Calculates the notional at the end of a period, given a period.NotionalFromComponent.getNotionalAtPeriodEnd
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) NotionalFromConstant.getNotionalAtPeriodEnd
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) AccruingNotional.getNotionalAtPeriodStart
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) Notional.getNotionalAtPeriodStart
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) Calculates the notional at the start of a period, given a period.NotionalFromComponent.getNotionalAtPeriodStart
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) NotionalFromConstant.getNotionalAtPeriodStart
(AbstractPeriod period, TermStructureMonteCarloSimulationModel model) abstract RandomVariable
AbstractPeriod.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) AccrualAccount.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) Cashflow.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Choice.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ExpectedTailLoss.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ExposureEstimator.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.IndexedValue.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Numeraire.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Option.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Period.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.ProductCollection.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime.Selector.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) This method returns the value random variable of the product within the specified model, evaluated at a given evalutationTime. -
Uses of RandomVariable in net.finmath.montecarlo.interestrate.products.indices
Modifier and TypeMethodDescriptionFixedCoupon.getCoupon()
Returns the coupon.abstract RandomVariable
AbstractIndex.getValue
(double fixingTime, TermStructureMonteCarloSimulationModel model) AccruedInterest.getValue
(double fixingTime, TermStructureMonteCarloSimulationModel model) AnalyticModelForwardCurveIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) AnalyticModelIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) CappedFlooredIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) ConstantMaturitySwaprate.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) DateIndex.getValue
(double fixingTime, TermStructureMonteCarloSimulationModel model) FixedCoupon.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) ForwardCurveIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) LaggedIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) LIBORIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) LinearCombinationIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) MaxIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) MinIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) NumerairePerformanceIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) NumerairePerformanceOnScheduleIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) PerformanceIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) PowIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) ProductIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) TimeDiscreteEndOfMonthIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) TriggerIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) UnsupportedIndex.getValue
(double evaluationTime, TermStructureMonteCarloSimulationModel model) -
Uses of RandomVariable in net.finmath.montecarlo.model
Modifier and TypeMethodDescriptionProcessModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) Applies the state space transform fi to the given state random variable such that Yi → fi(Yi) =: Xi.default RandomVariable
ProcessModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) Applies the inverse state space transform f-1i to the given random variable such that Xi → f-1i(Xi) =: Yi.ProcessModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) This method has to be implemented to return the drift, i.e.ProcessModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) This method has to be implemented to return the factor loadings, i.e.ProcessModel.getInitialState
(MonteCarloProcess process) Returns the initial value of the state variable of the process Y, not to be confused with the initial value of the model X (which is the state space transform applied to this state value.AbstractProcessModel.getInitialValue
(MonteCarloProcess process) Returns the initial value of the model.ProcessModel.getNumeraire
(MonteCarloProcess process, double time) Return the numeraire at a given time index.ProcessModel.getRandomVariableForConstant
(double value) Return a random variable initialized with a constant using the models random variable factory.Modifier and TypeMethodDescriptionProcessModel.applyStateSpaceTransform
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) Applies the state space transform fi to the given state random variable such that Yi → fi(Yi) =: Xi.default RandomVariable
ProcessModel.applyStateSpaceTransformInverse
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable randomVariable) Applies the inverse state space transform f-1i to the given random variable such that Xi → f-1i(Xi) =: Yi.ProcessModel.getDrift
(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) This method has to be implemented to return the drift, i.e.ProcessModel.getFactorLoading
(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) This method has to be implemented to return the factor loadings, i.e. -
Uses of RandomVariable in net.finmath.montecarlo.process
Modifier and TypeMethodDescriptionMonteCarloProcessFromProcessModel.applyStateSpaceTransform
(int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloProcessFromProcessModel.applyStateSpaceTransformInverse
(int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloProcessFromProcessModel.getDrift
(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloProcessFromProcessModel.getFactorLoading
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) MonteCarloProcessFromProcessModel.getInitialState()
EulerSchemeFromProcessModel.getMonteCarloWeights
(int timeIndex) This method returns the weights of a weighted Monte Carlo method (the probability density).LinearInterpolatedTimeDiscreteProcess.getMonteCarloWeights
(int timeIndex) Process.getMonteCarloWeights
(int timeIndex) This method returns the weights of a weighted Monte Carlo method (the probability density).EulerSchemeFromProcessModel.getProcessValue
(int timeIndex, int componentIndex) This method returns the realization of the process at a certain time index.LinearInterpolatedTimeDiscreteProcess.getProcessValue
(double time, int component) Returns the (possibly interpolated) value of this stochastic process at a given time \( t \).LinearInterpolatedTimeDiscreteProcess.getProcessValue
(int timeIndex, int component) default RandomVariable[]
Process.getProcessValue
(int timeIndex) This method returns the realization of the process for a given time index.Process.getProcessValue
(int timeIndex, int componentIndex) This method returns the realization of a component of the process for a given time index.Modifier and TypeMethodDescriptionMonteCarloProcessFromProcessModel.applyStateSpaceTransform
(int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloProcessFromProcessModel.applyStateSpaceTransformInverse
(int timeIndex, int componentIndex, RandomVariable randomVariable) MonteCarloProcessFromProcessModel.getDrift
(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloProcessFromProcessModel.getFactorLoading
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex) ModifierConstructorDescriptionLinearInterpolatedTimeDiscreteProcess
(Map<Double, RandomVariable> realizations) Create a time discrete process by linear interpolation of random variables. -
Uses of RandomVariable in net.finmath.montecarlo.process.component.barrier
Modifier and TypeMethodDescriptionBarrier.getBarrierLevel
(int timeIndex, RandomVariable[] randomVariable) The barrier levelModifier and TypeMethodDescriptionBarrier.getBarrierDirection
(int timeIndex, RandomVariable[] randomVariable) The barrier direction, i.e.Barrier.getBarrierLevel
(int timeIndex, RandomVariable[] randomVariable) The barrier level -
Uses of RandomVariable in net.finmath.montecarlo.process.component.factortransform
Modifier and TypeMethodDescriptionFactorTransform.getFactorDrift
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.FactorTransform.getFactorDriftDeterminant
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.FactorTransform.getFactorScaling
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor scaling may be specified for the generation of a process (see e.g.Modifier and TypeMethodDescriptionFactorTransform.getFactorDrift
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.FactorTransform.getFactorDriftDeterminant
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor drift may be specified for the generation of a process (see e.g.FactorTransform.getFactorScaling
(int timeIndex, RandomVariable[] realizationPredictor) The interface describes how an additional factor scaling may be specified for the generation of a process (see e.g. -
Uses of RandomVariable in net.finmath.montecarlo.products
Modifier and TypeMethodDescriptionPortfolioMonteCarloProduct.getValue
(double evaluationTime, MonteCarloSimulationModel model) -
Uses of RandomVariable in net.finmath.montecarlo.templatemethoddesign
Modifier and TypeMethodDescriptionabstract RandomVariable
LogNormalProcess.getDrift
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) LogNormalProcess.getDrift
(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Get the the drift.abstract RandomVariable
LogNormalProcess.getFactorLoading
(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex) This method should be overwritten and return the factor loading, i.e.abstract RandomVariable[]
LogNormalProcess.getInitialValue()
LogNormalProcess.getMonteCarloWeights
(int timeIndex) This method returns the weights of a weighted Monte Carlo method (the probability density).LogNormalProcess.getProcessValue
(int timeIndex) This method returns the realization of the process at a certain time index.LogNormalProcess.getProcessValue
(int timeIndex, int componentIndex) This method returns the realization of the process at a certain time index.Modifier and TypeMethodDescriptionabstract RandomVariable
LogNormalProcess.getDrift
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) LogNormalProcess.getDrift
(int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) Get the the drift.abstract RandomVariable
LogNormalProcess.getFactorLoading
(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex) This method should be overwritten and return the factor loading, i.e. -
Uses of RandomVariable in net.finmath.montecarlo.templatemethoddesign.assetderivativevaluation
Modifier and TypeMethodDescriptionMonteCarloBlackScholesModel2.getAssetValue
(double time, int assetIndex) MonteCarloBlackScholesModel2.getAssetValue
(int timeIndex, int assetIndex) MonteCarloBlackScholesModel2.getDrift
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloBlackScholesModel2.getFactorLoading
(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex) MonteCarloBlackScholesModel2.getInitialValue()
MonteCarloBlackScholesModel2.getMonteCarloWeights
(double time) MonteCarloBlackScholesModel2.getNumeraire
(double time) MonteCarloBlackScholesModel2.getNumeraire
(int timeIndex) MonteCarloBlackScholesModel2.getRandomVariableForConstant
(double value) Modifier and TypeMethodDescriptionMonteCarloBlackScholesModel2.getDrift
(int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor) MonteCarloBlackScholesModel2.getFactorLoading
(int timeIndex, int factor, int component, RandomVariable[] realizationAtTimeIndex) -
Uses of RandomVariable in net.finmath.optimizer
Modifier and TypeMethodDescriptionStochasticLevenbergMarquardt.getBestFitParameters()
StochasticOptimizer.getBestFitParameters()
Get the best fit parameter vector.StochasticPathwiseLevenbergMarquardt.getBestFitParameters()
StochasticPathwiseLevenbergMarquardt.getMeanSquaredError
(RandomVariable[] value) Modifier and TypeMethodDescriptionStochasticLevenbergMarquardt.getCloneWithModifiedTargetValues
(RandomVariable[] newTargetVaues, RandomVariable[] newWeights, boolean isUseBestParametersAsInitialParameters) Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.StochasticPathwiseLevenbergMarquardt.getCloneWithModifiedTargetValues
(RandomVariable[] newTargetVaues, RandomVariable[] newWeights, boolean isUseBestParametersAsInitialParameters) Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.double
StochasticLevenbergMarquardt.getMeanSquaredError
(RandomVariable[] value) StochasticPathwiseLevenbergMarquardt.getMeanSquaredError
(RandomVariable[] value) default StochasticOptimizer
StochasticOptimizerFactory.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues) default StochasticOptimizer
StochasticOptimizerFactory.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues) StochasticOptimizerFactory.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterStep, RandomVariable[] targetValues) StochasticOptimizerFactoryLevenbergMarquardt.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues) StochasticOptimizerFactoryLevenbergMarquardtAD.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues) StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues) StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues) StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues) StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] targetValues) StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] targetValues) StochasticPathwiseOptimizerFactoryLevenbergMarquardt.getOptimizer
(StochasticOptimizer.ObjectiveFunction objectiveFunction, RandomVariable[] initialParameters, RandomVariable[] lowerBound, RandomVariable[] upperBound, RandomVariable[] parameterSteps, RandomVariable[] targetValues) protected void
StochasticLevenbergMarquardt.prepareAndSetDerivatives
(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives) protected void
StochasticLevenbergMarquardtAD.prepareAndSetDerivatives
(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives) protected void
StochasticPathwiseLevenbergMarquardt.prepareAndSetDerivatives
(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives) protected void
StochasticPathwiseLevenbergMarquardtAD.prepareAndSetDerivatives
(RandomVariable[] parameters, RandomVariable[] values, RandomVariable[][] derivatives) protected void
StochasticLevenbergMarquardt.prepareAndSetValues
(RandomVariable[] parameters, RandomVariable[] values) protected void
StochasticLevenbergMarquardtAD.prepareAndSetValues
(RandomVariable[] parameters, RandomVariable[] values) protected void
StochasticPathwiseLevenbergMarquardt.prepareAndSetValues
(RandomVariable[] parameters, RandomVariable[] values) protected void
StochasticPathwiseLevenbergMarquardtAD.prepareAndSetValues
(RandomVariable[] parameters, RandomVariable[] values) void
StochasticLevenbergMarquardt.setDerivatives
(RandomVariable[] parameters, RandomVariable[][] derivatives) The derivative of the objective function.void
StochasticPathwiseLevenbergMarquardt.setDerivatives
(RandomVariable[] parameters, RandomVariable[][] derivatives) The derivative of the objective function.void
StochasticPathwiseLevenbergMarquardt.setErrorMeanSquaredCurrent
(RandomVariable errorMeanSquaredCurrent) abstract void
StochasticLevenbergMarquardt.setValues
(RandomVariable[] parameters, RandomVariable[] values) The objective function.void
StochasticOptimizer.ObjectiveFunction.setValues
(RandomVariable[] parameters, RandomVariable[] values) abstract void
StochasticPathwiseLevenbergMarquardt.setValues
(RandomVariable[] parameters, RandomVariable[] values) The objective function.Modifier and TypeMethodDescriptionStochasticLevenbergMarquardt.getCloneWithModifiedTargetValues
(List<RandomVariable> newTargetVaues, List<RandomVariable> newWeights, boolean isUseBestParametersAsInitialParameters) Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.StochasticPathwiseLevenbergMarquardt.getCloneWithModifiedTargetValues
(List<RandomVariable> newTargetVaues, List<RandomVariable> newWeights, boolean isUseBestParametersAsInitialParameters) Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.ModifierConstructorDescriptionStochasticLevenbergMarquardt
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, int numberOfThreads) Create a Levenberg-Marquardt solver.StochasticLevenbergMarquardt
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService) Create a Levenberg-Marquardt solver.StochasticLevenbergMarquardt
(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService) Create a Levenberg-Marquardt solver.StochasticLevenbergMarquardtAD
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService) StochasticLevenbergMarquardtAD
(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService, boolean isGradientValuationParallel) StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD
(int maxIterations, RandomVariable errorTolerance, int maxThreads) StochasticPathwiseLevenbergMarquardt
(RandomVariable[] initialParameters, RandomVariable[] targetValues, int maxIteration, int numberOfThreads) Create a Levenberg-Marquardt solver.StochasticPathwiseLevenbergMarquardt
(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] weights, RandomVariable[] parameterSteps, int maxIteration, RandomVariable errorTolerance, ExecutorService executorService) Create a Levenberg-Marquardt solver.StochasticPathwiseLevenbergMarquardtAD
(RandomVariable[] initialParameters, RandomVariable[] targetValues, int maxIteration, int numberOfThreads) StochasticPathwiseLevenbergMarquardtAD
(RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] weights, RandomVariable[] parameterSteps, int maxIteration, RandomVariable errorTolerance, ExecutorService executorService) ModifierConstructorDescriptionStochasticPathwiseLevenbergMarquardt
(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, int numberOfThreads) Create a Levenberg-Marquardt solver.StochasticPathwiseLevenbergMarquardt
(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, ExecutorService executorService) Create a Levenberg-Marquardt solver.StochasticPathwiseLevenbergMarquardtAD
(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, int numberOfThreads) StochasticPathwiseLevenbergMarquardtAD
(List<RandomVariable> initialParameters, List<RandomVariable> targetValues, int maxIteration, ExecutorService executorService) -
Uses of RandomVariable in net.finmath.stochastic
Modifier and TypeInterfaceDescriptioninterface
The interface implemented by a mutable random variable accumulator.interface
An array ofRandomVariable
objects, implementing theRandomVariable
interface.Modifier and TypeClassDescriptionclass
An implementation ofRandomVariableArray
implementing an array ofRandomVariable
objects, implementing theRandomVariable
interface.class
A scalar value implementing the RandomVariable.Modifier and TypeMethodDescriptionRandomVariable.abs()
Applies x → Math.abs(x), i.e.RandomVariableArrayImplementation.abs()
Scalar.abs()
RandomVariable.accrue
(RandomVariable rate, double periodLength) Applies x → x * (1.0 + rate * periodLength) to this random variable.RandomVariableArrayImplementation.accrue
(RandomVariable rate, double periodLength) Scalar.accrue
(RandomVariable rate, double periodLength) RandomVariable.add
(double value) Applies x → x + value to this random variable.RandomVariable.add
(RandomVariable randomVariable) Applies x → x+randomVariable to this random variable.RandomVariableArrayImplementation.add
(double value) RandomVariableArrayImplementation.add
(RandomVariable randomVariable) Scalar.add
(double value) Scalar.add
(RandomVariable randomVariable) RandomVariable.addProduct
(RandomVariable factor1, double factor2) Applies x → x + factor1 * factor2RandomVariable.addProduct
(RandomVariable factor1, RandomVariable factor2) Applies x → x + factor1 * factor2RandomVariableArrayImplementation.addProduct
(RandomVariable factor1, double factor2) RandomVariableArrayImplementation.addProduct
(RandomVariable factor1, RandomVariable factor2) Scalar.addProduct
(RandomVariable factor1, double factor2) Scalar.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariable.addRatio
(RandomVariable numerator, RandomVariable denominator) Applies x → x + numerator / denominatorRandomVariableArrayImplementation.addRatio
(RandomVariable numerator, RandomVariable denominator) Scalar.addRatio
(RandomVariable numerator, RandomVariable denominator) default RandomVariable
RandomVariable.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}default RandomVariable
RandomVariable.addSumProduct
(RandomVariable[] factor1, RandomVariable[] factor2) Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}RandomOperator.apply
(RandomVariable value) Applies this function to the given argument.RandomVariable.apply
(DoubleBinaryOperator operator, RandomVariable argument) Applies x → operator(x,y) to this random variable, where x is this random variable and y is a given random variable.RandomVariable.apply
(DoubleUnaryOperator operator) Applies x → operator(x) to this random variable.RandomVariable.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable.RandomVariableArrayImplementation.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableArrayImplementation.apply
(DoubleUnaryOperator operator) RandomVariableArrayImplementation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Scalar.apply
(DoubleBinaryOperator operator, RandomVariable argument) Scalar.apply
(DoubleUnaryOperator operator) Scalar.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) default RandomVariable
RandomVariable.appy
(RandomOperator operator) Applies x → operator(x) to this random variable.RandomVariable.average()
Returns a random variable which is deterministic and corresponds the expectation of this random variable.RandomVariableArrayImplementation.average()
Scalar.average()
default RandomVariable
RandomVariable.bus
(double value) Applies x → value - x to this random variable.RandomVariable.bus
(RandomVariable randomVariable) Applies x → randomVariable-x to this random variable.RandomVariableArrayImplementation.bus
(RandomVariable randomVariable) Scalar.bus
(RandomVariable randomVariable) RandomVariable.cache()
Return a cacheable version of this object (often a self-reference).RandomVariableArrayImplementation.cache()
Scalar.cache()
RandomVariable.cap
(double cap) Applies x → min(x,cap) to this random variable.RandomVariable.cap
(RandomVariable cap) Applies x → min(x,cap) to this random variable.RandomVariableArrayImplementation.cap
(double cap) RandomVariableArrayImplementation.cap
(RandomVariable cap) Scalar.cap
(double cap) Scalar.cap
(RandomVariable cap) RandomVariable.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) Applies x → (x ≥ 0 ? valueIfTriggerNonNegative : valueIfTriggerNegative)RandomVariableArrayImplementation.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) Scalar.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) RandomVariable.cos()
Applies x → cos(x) to this random variable.RandomVariableArrayImplementation.cos()
Scalar.cos()
default RandomVariable
RandomVariable.covariance
(RandomVariable value) Returns a random variable which is deterministic and corresponds the covariance of this random variable and the argument.RandomVariable.discount
(RandomVariable rate, double periodLength) Applies x → x / (1.0 + rate * periodLength) to this random variable.RandomVariableArrayImplementation.discount
(RandomVariable rate, double periodLength) Scalar.discount
(RandomVariable rate, double periodLength) RandomVariable.div
(double value) Applies x → x / value to this random variable.RandomVariable.div
(RandomVariable randomVariable) Applies x → x/randomVariable to this random variable.RandomVariableArrayImplementation.div
(double value) RandomVariableArrayImplementation.div
(RandomVariable randomVariable) Scalar.div
(double value) Scalar.div
(RandomVariable randomVariable) RandomVariable.exp()
Applies x → exp(x) to this random variable.RandomVariableArrayImplementation.exp()
Scalar.exp()
default RandomVariable
RandomVariable.expectation()
Returns a random variable which is deterministic and corresponds the expectation of this random variable.default RandomVariable
RandomVariable.expm1()
Applies x → expm1(x) (that is x → exp(x)-1.0) to this random variable.Scalar.expm1()
RandomVariable.floor
(double floor) Applies x → max(x,floor) to this random variable.RandomVariable.floor
(RandomVariable floor) Applies x → max(x,floor) to this random variable.RandomVariableArrayImplementation.floor
(double floor) RandomVariableArrayImplementation.floor
(RandomVariable floor) Scalar.floor
(double floor) Scalar.floor
(RandomVariable floor) RandomVariableAccumulator.get()
RandomVariableAccumulator.get
(double fromTime, double toTime) ConditionalExpectationEstimator.getConditionalExpectation
(RandomVariable randomVariable) Return the conditional expectation of a given random variable.default RandomVariable
RandomVariable.getConditionalExpectation
(ConditionalExpectationEstimator conditionalExpectationOperator) Returns the conditional expectation using a given conditional expectation estimator.RandomVariableArray.getElement
(int index) RandomVariableArrayImplementation.getElement
(int index) default RandomVariable
RandomVariable.getValues()
Returns the underlying values and a random variable.RandomVariable.invert()
Applies x → 1/x to this random variable.RandomVariableArrayImplementation.invert()
Scalar.invert()
RandomVariable.isNaN()
Applies x → (Double.isNaN(x) ? 1.0 : 0.0)RandomVariableArrayImplementation.isNaN()
Scalar.isNaN()
RandomVariable.log()
Applies x → log(x) to this random variable.RandomVariableArrayImplementation.log()
Scalar.log()
RandomVariable.mult
(double value) Applies x → x * value to this random variable.RandomVariable.mult
(RandomVariable randomVariable) Applies x → x*randomVariable to this random variable.RandomVariableArrayImplementation.mult
(double value) RandomVariableArrayImplementation.mult
(RandomVariable randomVariable) Scalar.mult
(double value) Scalar.mult
(RandomVariable randomVariable) RandomVariable.pow
(double exponent) Applies x → pow(x,exponent) to this random variable.RandomVariableArrayImplementation.pow
(double exponent) Scalar.pow
(double exponent) RandomVariable.sin()
Applies x → sin(x) to this random variable.RandomVariableArrayImplementation.sin()
Scalar.sin()
RandomVariable.sqrt()
Applies x → sqrt(x) to this random variable.RandomVariableArrayImplementation.sqrt()
Scalar.sqrt()
RandomVariable.squared()
Applies x → x * x to this random variable.RandomVariableArrayImplementation.squared()
Scalar.squared()
RandomVariable.sub
(double value) Applies x → x - value to this random variable.RandomVariable.sub
(RandomVariable randomVariable) Applies x → x-randomVariable to this random variable.RandomVariableArrayImplementation.sub
(double value) RandomVariableArrayImplementation.sub
(RandomVariable randomVariable) Scalar.sub
(double value) Scalar.sub
(RandomVariable randomVariable) RandomVariable.subRatio
(RandomVariable numerator, RandomVariable denominator) Applies x → x - numerator / denominatorRandomVariableArrayImplementation.subRatio
(RandomVariable numerator, RandomVariable denominator) Scalar.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariableArray.sumProduct
(RandomVariableArray array) Components wise product followed by sum of all elements.RandomVariableArrayImplementation.sumProduct
(RandomVariableArray array) default RandomVariable
RandomVariable.variance()
Returns a random variable which is deterministic and corresponds the variance of this random variable.default RandomVariable
RandomVariable.vid
(double value) Applies x → value / x to this random variable.RandomVariable.vid
(RandomVariable randomVariable) Applies x → randomVariable/x to this random variable.RandomVariableArrayImplementation.vid
(RandomVariable randomVariable) Scalar.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptionRandomVariable.accrue
(RandomVariable rate, double periodLength) Applies x → x * (1.0 + rate * periodLength) to this random variable.RandomVariableArrayImplementation.accrue
(RandomVariable rate, double periodLength) Scalar.accrue
(RandomVariable rate, double periodLength) void
RandomVariableAccumulator.accumulate
(double time, RandomVariable randomVariable) void
RandomVariableAccumulator.accumulate
(RandomVariable randomVariable) RandomVariable.add
(RandomVariable randomVariable) Applies x → x+randomVariable to this random variable.RandomVariableArrayImplementation.add
(RandomVariable randomVariable) Scalar.add
(RandomVariable randomVariable) RandomVariable.addProduct
(RandomVariable factor1, double factor2) Applies x → x + factor1 * factor2RandomVariable.addProduct
(RandomVariable factor1, RandomVariable factor2) Applies x → x + factor1 * factor2RandomVariableArrayImplementation.addProduct
(RandomVariable factor1, double factor2) RandomVariableArrayImplementation.addProduct
(RandomVariable factor1, RandomVariable factor2) Scalar.addProduct
(RandomVariable factor1, double factor2) Scalar.addProduct
(RandomVariable factor1, RandomVariable factor2) RandomVariable.addRatio
(RandomVariable numerator, RandomVariable denominator) Applies x → x + numerator / denominatorRandomVariableArrayImplementation.addRatio
(RandomVariable numerator, RandomVariable denominator) Scalar.addRatio
(RandomVariable numerator, RandomVariable denominator) default RandomVariable
RandomVariable.addSumProduct
(RandomVariable[] factor1, RandomVariable[] factor2) Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}RandomOperator.apply
(RandomVariable value) Applies this function to the given argument.RandomVariable.apply
(DoubleBinaryOperator operator, RandomVariable argument) Applies x → operator(x,y) to this random variable, where x is this random variable and y is a given random variable.RandomVariable.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable.RandomVariableArrayImplementation.apply
(DoubleBinaryOperator operator, RandomVariable argument) RandomVariableArrayImplementation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Scalar.apply
(DoubleBinaryOperator operator, RandomVariable argument) Scalar.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariable.bus
(RandomVariable randomVariable) Applies x → randomVariable-x to this random variable.RandomVariableArrayImplementation.bus
(RandomVariable randomVariable) Scalar.bus
(RandomVariable randomVariable) RandomVariable.cap
(RandomVariable cap) Applies x → min(x,cap) to this random variable.RandomVariableArrayImplementation.cap
(RandomVariable cap) Scalar.cap
(RandomVariable cap) RandomVariable.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) Applies x → (x ≥ 0 ? valueIfTriggerNonNegative : valueIfTriggerNegative)RandomVariableArrayImplementation.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) Scalar.choose
(RandomVariable valueIfTriggerNonNegative, RandomVariable valueIfTriggerNegative) default RandomVariable
RandomVariable.covariance
(RandomVariable value) Returns a random variable which is deterministic and corresponds the covariance of this random variable and the argument.RandomVariable.discount
(RandomVariable rate, double periodLength) Applies x → x / (1.0 + rate * periodLength) to this random variable.RandomVariableArrayImplementation.discount
(RandomVariable rate, double periodLength) Scalar.discount
(RandomVariable rate, double periodLength) RandomVariable.div
(RandomVariable randomVariable) Applies x → x/randomVariable to this random variable.RandomVariableArrayImplementation.div
(RandomVariable randomVariable) Scalar.div
(RandomVariable randomVariable) boolean
RandomVariable.equals
(RandomVariable randomVariable) Compare this random variable with a given oneboolean
RandomVariableArrayImplementation.equals
(RandomVariable randomVariable) boolean
Scalar.equals
(RandomVariable randomVariable) RandomVariable.floor
(RandomVariable floor) Applies x → max(x,floor) to this random variable.RandomVariableArrayImplementation.floor
(RandomVariable floor) Scalar.floor
(RandomVariable floor) double
RandomVariable.getAverage
(RandomVariable probabilities) Returns the expectation of this random variable for a given probability measure (weight).double
RandomVariableArrayImplementation.getAverage
(RandomVariable probabilities) double
Scalar.getAverage
(RandomVariable probabilities) ConditionalExpectationEstimator.getConditionalExpectation
(RandomVariable randomVariable) Return the conditional expectation of a given random variable.double
RandomVariable.getQuantile
(double quantile, RandomVariable probabilities) Returns the quantile value for this given random variable, i.e., the value x such that P(this < x) = quantile, where P denotes the probability measure.double
RandomVariableArrayImplementation.getQuantile
(double quantile, RandomVariable probabilities) double
Scalar.getQuantile
(double quantile, RandomVariable probabilities) double
RandomVariable.getStandardDeviation
(RandomVariable probabilities) Returns the standard deviation of this random variable, i.e., sqrt(V) where V = ((X-m)^2).getAverage(probabilities) and X = this and m = X.getAverage(probabilities).double
RandomVariableArrayImplementation.getStandardDeviation
(RandomVariable probabilities) double
Scalar.getStandardDeviation
(RandomVariable probabilities) double
RandomVariable.getStandardError
(RandomVariable probabilities) Returns the standard error (discretization error) of this random variable.double
RandomVariableArrayImplementation.getStandardError
(RandomVariable probabilities) double
Scalar.getStandardError
(RandomVariable probabilities) double
RandomVariable.getVariance
(RandomVariable probabilities) Returns the variance of this random variable, i.e., V where V = ((X-m)^2).getAverage(probabilities) and X = this and m = X.getAverage(probabilities).double
RandomVariableArrayImplementation.getVariance
(RandomVariable probabilities) double
Scalar.getVariance
(RandomVariable probabilities) RandomVariable.mult
(RandomVariable randomVariable) Applies x → x*randomVariable to this random variable.RandomVariableArrayImplementation.mult
(RandomVariable randomVariable) Scalar.mult
(RandomVariable randomVariable) static RandomVariableArray
RandomVariableArrayImplementation.of
(RandomVariable[] elements) RandomVariable.sub
(RandomVariable randomVariable) Applies x → x-randomVariable to this random variable.RandomVariableArrayImplementation.sub
(RandomVariable randomVariable) Scalar.sub
(RandomVariable randomVariable) RandomVariable.subRatio
(RandomVariable numerator, RandomVariable denominator) Applies x → x - numerator / denominatorRandomVariableArrayImplementation.subRatio
(RandomVariable numerator, RandomVariable denominator) Scalar.subRatio
(RandomVariable numerator, RandomVariable denominator) RandomVariable.vid
(RandomVariable randomVariable) Applies x → randomVariable/x to this random variable.RandomVariableArrayImplementation.vid
(RandomVariable randomVariable) Scalar.vid
(RandomVariable randomVariable) Modifier and TypeMethodDescriptiondefault RandomVariable
RandomVariable.addSumProduct
(List<RandomVariable> factor1, List<RandomVariable> factor2) Applies \( x \mapsto x + \sum_{i=0}^{n-1} factor1_{i} * factor2_{i}