A B C D E F G I L M N O P R S T

A

abs() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

abs() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

AbstractRandomVariableDifferentiableFactory - Class in net.finmath.montecarlo.automaticdifferentiation

A random variable factory extending AbstractRandomVariableFactory providing random variables implementing RandomVariableDifferentiableInterface.

AbstractRandomVariableDifferentiableFactory(AbstractRandomVariableFactory) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

Construct an object extending AbstractRandomVariableDifferentiableFactory with a specific AbstractRandomVariableFactory for the storage of values.

AbstractRandomVariableDifferentiableFactory() - Constructor for class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

accrue(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

accrue(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

add(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

add(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

add(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

add(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

addProduct(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

addProduct(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

addProduct(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

addProduct(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

addRatio(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

addRatio(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

apply(DoubleUnaryOperator) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

apply(DoubleBinaryOperator, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

apply(DoubleTernaryOperator, RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

apply(DoubleUnaryOperator) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

apply(DoubleBinaryOperator, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

apply(DoubleTernaryOperator, RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

average() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

average() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

B

barrier(RandomVariableInterface, RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

barrier(RandomVariableInterface, RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

barrier(RandomVariableInterface, RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

barrier(RandomVariableInterface, RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

C

cache() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

cache() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

cap(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

cap(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

cap(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

cap(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

cos() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

cos() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

createRandomVariable(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

createRandomVariable(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

createRandomVariable(double, double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

createRandomVariable(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

createRandomVariable(double, double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

createRandomVariable(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableADFactory

createRandomVariable(double, double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableADFactory

createRandomVariableNonDifferentiable(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

createRandomVariableNonDifferentiable(double, double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.AbstractRandomVariableDifferentiableFactory

D

DeltaHedgedPortfolioWithAAD - Class in net.finmath.montecarlo.assetderivativevaluation.products

This class implements a delta hedged portfolio (a hedge simulator).

DeltaHedgedPortfolioWithAAD(AbstractAssetMonteCarloProduct) - Constructor for class net.finmath.montecarlo.assetderivativevaluation.products.DeltaHedgedPortfolioWithAAD

Construction of a delta hedge portfolio.

discount(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

discount(RandomVariableInterface, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

div(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

div(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

div(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

div(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

doubleValue() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

doubleValue() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

E

equals(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

equals(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

exp() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

exp() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

F

floor(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

floor(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

floor(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

floor(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

G

get(int) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

get(int) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getAverage() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getAverage(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getAverage() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getAverage(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getBarrierDiracWidth() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

getCloneIndependent() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getCloneIndependent() - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

Returns a clone of this differentiable random variable with a new ID.

getConditionalExpectation(ConditionalExpectationEstimatorInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getConditionalExpectation(ConditionalExpectationEstimatorInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getFactory() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getFiltrationTime() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getFiltrationTime() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getGradient(Set<Long>) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

Returns the gradient of this random variable with respect to all its leaf nodes.

getGradient(Set<Long>) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

Returns the gradient of this random variable with respect to all its leaf nodes.

getGradient() - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

Returns the gradient of this random variable with respect to all its leaf nodes.

getGradient(Set<Long>) - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

Returns the gradient of this random variable with respect to the given IDs.

getHistogram(double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getHistogram(int, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getHistogram(double[]) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getHistogram(int, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getID() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getID() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getID() - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

A unique id for this random variable.

getImpliedBachelierATMOptionVolatility(RandomVariableInterface, double, double) - Method in class net.finmath.montecarlo.interestrate.products.SwaptionATM

Calculates ATM Bachelier implied volatilities.

getLastOperationTimingDerivative() - Method in class net.finmath.montecarlo.assetderivativevaluation.products.DeltaHedgedPortfolioWithAAD

getLastOperationTimingValuation() - Method in class net.finmath.montecarlo.assetderivativevaluation.products.DeltaHedgedPortfolioWithAAD

getMax() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getMax() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getMaxAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getMaxAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getMin() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getMin() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getMinAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getMinAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getOperator() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getOperator() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getOperatorTreeNode() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getOperatorTreeNode() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getOptimizer(StochasticOptimizerInterface.ObjectiveFunction, RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticOptimizerFactoryLevenbergMarquardtAD

getOptimizer(StochasticOptimizerInterface.ObjectiveFunction, RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD

getOptimizer(StochasticOptimizerInterface.ObjectiveFunction, RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD

getOptimizer(StochasticOptimizerInterface.ObjectiveFunction, RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD

getQuantile(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getQuantile(double, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getQuantile(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getQuantile(double, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getQuantileExpectation(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getQuantileExpectation(double, double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getRandomVariable() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getRealizations() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getRealizations() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getRealizationsStream() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getRealizationsStream() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getSampleVariance() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getSampleVariance() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getSampleVarianceAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getSampleVarianceAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardDeviation() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardDeviation(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardDeviation() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardDeviation(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardDeviationAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardDeviationAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardError() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardError(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardError() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardError(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getStandardErrorAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getStandardErrorAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getTangents(Set<Long>) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getTangents(Set<Long>) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getTangents() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getTangents() - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

Returns the tangents of this random variable with respect to all its dependent nodes.

getTangents(Set<Long>) - Method in interface net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiableInterface

Returns the tangents of this random variable with respect to the given dependent node IDs (if dependent).

getValue(double, AssetModelMonteCarloSimulationInterface) - Method in class net.finmath.montecarlo.assetderivativevaluation.products.DeltaHedgedPortfolioWithAAD

getValue(double, LIBORModelMonteCarloSimulationInterface) - Method in class net.finmath.montecarlo.interestrate.products.SwaptionATM

getVariance() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getVariance(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getVariance() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getVariance(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

getVarianceAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

getVarianceAsRandomVariableAAD() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

I

invert() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

invert() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

isDeterministic() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

isDeterministic() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

isGradientRetainsLeafNodesOnly() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

isNaN() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

isNaN() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

L

log() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

log() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

M

mult(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

mult(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

mult(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

mult(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

N

net.finmath.montecarlo.assetderivativevaluation.products - package net.finmath.montecarlo.assetderivativevaluation.products

Products which may be valued using an AssetModelMonteCarloSimulationInterface.

net.finmath.montecarlo.automaticdifferentiation - package net.finmath.montecarlo.automaticdifferentiation

Provides classes adding automatic differentiation capabilities to objects relying on RandomVariableInterface objects.

net.finmath.montecarlo.automaticdifferentiation.backward - package net.finmath.montecarlo.automaticdifferentiation.backward

Provides the implementation of backward automatic differentiation.

net.finmath.montecarlo.automaticdifferentiation.forward - package net.finmath.montecarlo.automaticdifferentiation.forward

Provides the implementation of forward automatic differentiation.

net.finmath.montecarlo.interestrate.products - package net.finmath.montecarlo.interestrate.products

Provides classes which implement financial products which may be valued using a net.finmath.montecarlo.interestrate.LIBORModelMonteCarloSimulationInterface.

net.finmath.optimizer - package net.finmath.optimizer

This package provides classes with numerical algorithm for optimization of an objective function and a factory to easy construction of the optimizers.

O

of(double) - Static method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

of(RandomVariableInterface) - Static method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

of(double) - Static method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

of(RandomVariableInterface) - Static method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

P

pow(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

pow(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

prepareAndSetDerivatives(RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[][]) - Method in class net.finmath.optimizer.StochasticLevenbergMarquardtAD

prepareAndSetDerivatives(RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[][]) - Method in class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

prepareAndSetValues(RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticLevenbergMarquardtAD

prepareAndSetValues(RandomVariableInterface[], RandomVariableInterface[]) - Method in class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

R

RandomVariableDifferentiableAAD - Class in net.finmath.montecarlo.automaticdifferentiation.backward

Implementation of RandomVariableDifferentiableInterface using the backward algorithmic differentiation (adjoint algorithmic differentiation, AAD).

RandomVariableDifferentiableAAD(double) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

RandomVariableDifferentiableAAD(RandomVariableInterface) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

RandomVariableDifferentiableAAD(RandomVariableInterface, RandomVariableDifferentiableAADFactory) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

RandomVariableDifferentiableAAD(RandomVariableInterface, List<RandomVariableInterface>, ConditionalExpectationEstimatorInterface, RandomVariableDifferentiableAAD.OperatorType, RandomVariableDifferentiableAADFactory) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

RandomVariableDifferentiableAADFactory - Class in net.finmath.montecarlo.automaticdifferentiation.backward

RandomVariableDifferentiableAADFactory() - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

RandomVariableDifferentiableAADFactory(AbstractRandomVariableFactory) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

RandomVariableDifferentiableAADFactory(AbstractRandomVariableFactory, Map<String, Object>) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAADFactory

RandomVariableDifferentiableAD - Class in net.finmath.montecarlo.automaticdifferentiation.forward

Implementation of RandomVariableDifferentiableInterface using the forward algorithmic differentiation (AD).

RandomVariableDifferentiableAD(double) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

RandomVariableDifferentiableAD(double, double[]) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

RandomVariableDifferentiableAD(RandomVariableInterface) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

RandomVariableDifferentiableAD(RandomVariableInterface, List<RandomVariableInterface>, ConditionalExpectationEstimatorInterface, RandomVariableDifferentiableAD.OperatorType) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

RandomVariableDifferentiableADFactory - Class in net.finmath.montecarlo.automaticdifferentiation.forward

RandomVariableDifferentiableADFactory() - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableADFactory

RandomVariableDifferentiableADFactory(AbstractRandomVariableFactory) - Constructor for class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableADFactory

RandomVariableDifferentiableInterface - Interface in net.finmath.montecarlo.automaticdifferentiation

Interface providing additional methods for random variable implementing RandomVariableInterface allowing automatic differentiation.

S

sin() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

sin() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

size() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

size() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

sqrt() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

sqrt() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

squared() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

squared() - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

StochasticLevenbergMarquardtAD - Class in net.finmath.optimizer

This class implements a stochastic Levenberg Marquardt non-linear least-squares fit algorithm.

StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod, RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], int, double, ExecutorService, boolean) - Constructor for class net.finmath.optimizer.StochasticLevenbergMarquardtAD

StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod, RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], int, double, ExecutorService) - Constructor for class net.finmath.optimizer.StochasticLevenbergMarquardtAD

StochasticOptimizerFactoryLevenbergMarquardtAD - Class in net.finmath.optimizer

StochasticOptimizerFactoryLevenbergMarquardtAD(int, double, int) - Constructor for class net.finmath.optimizer.StochasticOptimizerFactoryLevenbergMarquardtAD

StochasticOptimizerFactoryLevenbergMarquardtAD(int, int) - Constructor for class net.finmath.optimizer.StochasticOptimizerFactoryLevenbergMarquardtAD

StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD - Class in net.finmath.optimizer

StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD(int, RandomVariableInterface, int) - Constructor for class net.finmath.optimizer.StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD

StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD(int, int) - Constructor for class net.finmath.optimizer.StochasticOptimizerFactoryPathwiseLevenbergMarquardtAD

StochasticPathwiseLevenbergMarquardtAD - Class in net.finmath.optimizer

This class implements a stochastic Levenberg Marquardt non-linear least-squares fit algorithm.

StochasticPathwiseLevenbergMarquardtAD(List<RandomVariableInterface>, List<RandomVariableInterface>, int, ExecutorService) - Constructor for class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

StochasticPathwiseLevenbergMarquardtAD(List<RandomVariableInterface>, List<RandomVariableInterface>, int, int) - Constructor for class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

StochasticPathwiseLevenbergMarquardtAD(RandomVariableInterface[], RandomVariableInterface[], int, int) - Constructor for class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

StochasticPathwiseLevenbergMarquardtAD(RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], RandomVariableInterface[], int, RandomVariableInterface, ExecutorService) - Constructor for class net.finmath.optimizer.StochasticPathwiseLevenbergMarquardtAD

sub(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

sub(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

sub(double) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

sub(RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

subRatio(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

subRatio(RandomVariableInterface, RandomVariableInterface) - Method in class net.finmath.montecarlo.automaticdifferentiation.forward.RandomVariableDifferentiableAD

SwaptionATM - Class in net.finmath.montecarlo.interestrate.products

A lightweight ATM swaption product used for calibration.

SwaptionATM(double[], SwaptionSimple.ValueUnit) - Constructor for class net.finmath.montecarlo.interestrate.products.SwaptionATM

T

toString() - Method in class net.finmath.montecarlo.automaticdifferentiation.backward.RandomVariableDifferentiableAAD

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