Class LIBORMarketModelFromCovarianceModel

  • All Implemented Interfaces:
    Serializable, IndependentModelParameterProvider, LIBORMarketModel, LIBORModel, TermStructureModel, ProcessModel

    public class LIBORMarketModelFromCovarianceModel
    extends AbstractProcessModel
    implements LIBORMarketModel, Serializable
    Implements a (generalized) LIBOR market model with generic covariance structure (lognormal, normal, displaced or stochastic volatility) with some drift approximation methods.

    In its default case the class specifies a multi-factor LIBOR market model in its log-normal formulation, that is Lj = exp(Yj) where \[ dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m} \]
    The model uses an LIBORCovarianceModel for the specification of 1,j,...,λm,j) as a covariance model. See ProcessModel for details on the implemented interface

    However, the class is more general:
    • The model may be log-normal or normal specification with a given local volatility.
    • The class implements different measure(drift) / numeraire pairs: terminal measure and spot measure.
    • The class allows to configure a discounting curve (e.g. for "OIS discounting") using a simple deterministic zero spread. In this case, the numeraire \( N(t) \) is adjusted by \( \exp( \int_0^t -\lambda(\tau) d\tau ) \).

    The class specifies a LIBOR market model, that is Lj = f(Yj) where
    • f is f(x) = exp(x) (default, log-normal LIBOR Market Model) or
    • f is f(x) = x (normal model, used if property.set("stateSpace","NORMAL"))
    and
    dYj = μj dt + λ1,j dW1 + ... + λm,j dWm

    see ProcessModel for details on the implemented interface.
    The model uses an AbstractLIBORCovarianceModel as a covariance model. If the covariance model is of type AbstractLIBORCovarianceModelParametric a calibration to swaptions can be performed.
    Note that λ may still depend on L, hence generating a log-normal dynamic for L even if the stateSpace property has been set to NORMAL.
    The map properties allows to configure the model. The following keys may be used:
    • measure: Possible values:
      • SPOT: Simulate under spot measure. In this case, the single curve numeraire is \( N(T_{i}) = \prod_{j=0}^{i-1} (1 + L(T_{j},T_{j+1};T_{j}) (T_{j+1}-T_{j})) \).
      • TERMINAL: Simulate under terminal measure. In this case, the single curve numeraire is \( N(T_{i}) = P(T_{n};T_{i}) = \prod_{j=i}^{n-1} (1 + L(T_{j},T_{j+1};T_{i}) (T_{j+1}-T_{j}))^{-1} \).
    • stateSpace: Possible values:
      • LOGNORMAL: The state space transform is set to exp, i.e., L = exp(Y). When the covariance model is deterministic, then this is the classical lognormal LIBOR market model. Note that the covariance model may still provide a local volatility function.
      • NORMAL: The state space transform is set to identity, i.e., L = Y. When the covariance model is deterministic, then this is a normal LIBOR market model. Note that the covariance model may still provide a local volatility function.
    • simulationTimeInterpolationMethod: Possible values:
      • ROUND_DOWN: \( L(S,T;t) \) is mapped to \( L(S,T,t_{j}) \) with \( t_{j} \) being the largest time in the time discretization such that \( t_{j} \leq t \).
      • ROUND_NEAREST: \( L(S,T;t) \) is mapped to \( L(S,T,t_{j}) \) with \( t_{j} \) being the nearest time in the time discretization.
    • liborCap: An optional Double value applied as a cap to the LIBOR rates. May be used to limit the simulated valued to prevent values attaining POSITIVE_INFINITY and numerical problems. To disable the cap, set liborCap to Double.POSITIVE_INFINITY.

    The main task of this class is to calculate the risk-neutral drift and the corresponding numeraire given the covariance model. The calibration of the covariance structure is not part of this class. For the calibration of parametric models of the instantaneous covariance see AbstractLIBORCovarianceModelParametric.getCloneCalibrated(LIBORMarketModel, CalibrationProduct[], Map).
    Version:
    1.2
    Author:
    Christian Fries
    See Also:
    The interface for numerical schemes., The interface for models provinding parameters to numerical schemes., The abstract covariance model plug ins., A parametic covariance model including a generic calibration algorithm., Serialized Form
    • Constructor Detail

      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   AnalyticModel analyticModel,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   RandomVariableFactory randomVariableFactory,
                                                   LIBORCovarianceModel covarianceModel,
                                                   CalibrationProduct[] calibrationProducts,
                                                   Map<String,​?> properties)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance.
        If calibrationItems in non-empty and the covariance model is a parametric model, the covariance will be replaced by a calibrate version of the same model, i.e., the LIBOR Market Model will be calibrated.
        The map properties allows to configure the model. The following keys may be used:
        • measure: Possible values:
          • SPOT (String): Simulate under spot measure.
          • TERMINAL (String): Simulate under terminal measure.
        • stateSpace: Possible values:
          • LOGNORMAL (String): Simulate L = exp(Y).
          • NORMAL (String): Simulate L = Y.
        • liborCap: An optional Double value applied as a cap to the LIBOR rates. May be used to limit the simulated valued to prevent values attaining POSITIVE_INFINITY and numerical problems. To disable the cap, set liborCap to Double.POSITIVE_INFINITY.
        • calibrationParameters: Possible values:
          • Map<String,Object> a parameter map with the following key/value pairs:
            • accuracy: Double specifying the required solver accuracy.
            • maxIterations: Integer specifying the maximum iterations for the solver.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        analyticModel - The associated analytic model of this model (containing the associated market data objects like curve).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        randomVariableFactory - The random variable factory used to create the initial values of the model.
        covarianceModel - The covariance model to use.
        calibrationProducts - The vector of calibration items (a union of a product, target value and weight) for the objective function sum weight(i) * (modelValue(i)-targetValue(i).
        properties - Key value map specifying properties like measure and stateSpace.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   AnalyticModel analyticModel,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   RandomVariableFactory randomVariableFactory,
                                                   LIBORCovarianceModel covarianceModel,
                                                   Map<String,​?> properties)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance. The map properties allows to configure the model. The following keys may be used:
        • measure: Possible values:
          • SPOT (String): Simulate under spot measure.
          • TERMINAL (String): Simulate under terminal measure.
        • stateSpace: Possible values:
          • LOGNORMAL (String): Simulate L = exp(Y).
          • NORMAL (String): Simulate L = Y.
        • liborCap: An optional Double value applied as a cap to the LIBOR rates. May be used to limit the simulated valued to prevent values attaining POSITIVE_INFINITY and numerical problems. To disable the cap, set liborCap to Double.POSITIVE_INFINITY.
        • calibrationParameters: Possible values:
          • Map<String,Object> a parameter map with the following key/value pairs:
            • accuracy: Double specifying the required solver accuracy.
            • maxIterations: Integer specifying the maximum iterations for the solver.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        analyticModel - The associated analytic model of this model (containing the associated market data objects like curve).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        randomVariableFactory - The random variable factory used to create the initial values of the model.
        covarianceModel - The covariance model to use.
        properties - Key value map specifying properties like measure and stateSpace.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        @Deprecated
        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   AnalyticModel analyticModel,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   LIBORCovarianceModel covarianceModel,
                                                   CalibrationProduct[] calibrationItems,
                                                   Map<String,​?> properties)
                                            throws CalculationException
        Deprecated.
        Use LIBORMarketModelFromCovarianceModel.of() instead.
        Creates a LIBOR Market Model for given covariance.
        If calibrationItems in non-empty and the covariance model is a parametric model, the covariance will be replaced by a calibrate version of the same model, i.e., the LIBOR Market Model will be calibrated.
        The map properties allows to configure the model. The following keys may be used:
        • measure: Possible values:
          • SPOT (String): Simulate under spot measure.
          • TERMINAL (String): Simulate under terminal measure.
        • stateSpace: Possible values:
          • LOGNORMAL (String): Simulate L = exp(Y).
          • NORMAL (String): Simulate L = Y.
        • liborCap: An optional Double value applied as a cap to the LIBOR rates. May be used to limit the simulated valued to prevent values attaining POSITIVE_INFINITY and numerical problems. To disable the cap, set liborCap to Double.POSITIVE_INFINITY.
        • calibrationParameters: Possible values:
          • Map<String,Object> a parameter map with the following key/value pairs:
            • accuracy: Double specifying the required solver accuracy.
            • maxIterations: Integer specifying the maximum iterations for the solver.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        analyticModel - The associated analytic model of this model (containing the associated market data objects like curve).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        covarianceModel - The covariance model to use.
        calibrationItems - The vector of calibration items (a union of a product, target value and weight) for the objective function sum weight(i) * (modelValue(i)-targetValue(i).
        properties - Key value map specifying properties like measure and stateSpace.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   LIBORCovarianceModel covarianceModel)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        covarianceModel - The covariance model to use.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   LIBORCovarianceModel covarianceModel)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        covarianceModel - The covariance model to use.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   LIBORCovarianceModel covarianceModel,
                                                   SwaptionMarketData swaptionMarketData)
                                            throws CalculationException
        Creates a LIBOR Market Model using a given covariance model and calibrating this model to given swaption volatility data.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        covarianceModel - The covariance model to use.
        swaptionMarketData - The set of swaption values to calibrate to.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   LIBORCovarianceModel covarianceModel,
                                                   SwaptionMarketData swaptionMarketData)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        covarianceModel - The covariance model to use.
        swaptionMarketData - The set of swaption values to calibrate to.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   LIBORCovarianceModel covarianceModel,
                                                   SwaptionMarketData swaptionMarketData,
                                                   Map<String,​?> properties)
                                            throws CalculationException
        Creates a LIBOR Market Model for given covariance.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        covarianceModel - The covariance model to use.
        swaptionMarketData - The set of swaption values to calibrate to.
        properties - Key value map specifying properties like measure and stateSpace.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • LIBORMarketModelFromCovarianceModel

        @Deprecated
        public LIBORMarketModelFromCovarianceModel​(TimeDiscretization liborPeriodDiscretization,
                                                   ForwardCurve forwardRateCurve,
                                                   DiscountCurve discountCurve,
                                                   LIBORCovarianceModel covarianceModel,
                                                   CalibrationProduct[] calibrationItems,
                                                   Map<String,​?> properties)
                                            throws CalculationException
        Deprecated.
        Use LIBORMarketModelFromCovarianceModel.of() instead.
        Creates a LIBOR Market Model for given covariance.
        If calibrationItems in non-empty and the covariance model is a parametric model, the covariance will be replaced by a calibrate version of the same model, i.e., the LIBOR Market Model will be calibrated.
        The map properties allows to configure the model. The following keys may be used:
        • measure: Possible values:
          • SPOT (String): Simulate under spot measure.
          • TERMINAL (String): Simulate under terminal measure.
        • stateSpace: Possible values:
          • LOGNORMAL (String): Simulate L = exp(Y).
          • NORMAL (String): Simulate L = Y.
        • calibrationParameters: Possible values:
          • Map<String,Object> a parameter map with the following key/value pairs:
            • accuracy: Double specifying the required solver accuracy.
            • maxIterations: Integer specifying the maximum iterations for the solver.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        covarianceModel - The covariance model to use.
        calibrationItems - The vector of calibration items (a union of a product, target value and weight) for the objective function sum weight(i) * (modelValue(i)-targetValue(i).
        properties - Key value map specifying properties like measure and stateSpace.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
    • Method Detail

      • of

        public static LIBORMarketModelFromCovarianceModel of​(TimeDiscretization liborPeriodDiscretization,
                                                             AnalyticModel analyticModel,
                                                             ForwardCurve forwardRateCurve,
                                                             DiscountCurve discountCurve,
                                                             RandomVariableFactory randomVariableFactory,
                                                             LIBORCovarianceModel covarianceModel,
                                                             CalibrationProduct[] calibrationProducts,
                                                             Map<String,​?> properties)
                                                      throws CalculationException
        Creates a LIBOR Market Model for given covariance with a calibration (if calibration items are given).
        If calibrationItems in non-empty and the covariance model is a parametric model, the covariance will be replaced by a calibrate version of the same model, i.e., the LIBOR Market Model will be calibrated. Note: Calibration is not lazy.
        The map properties allows to configure the model. The following keys may be used:
        • measure: Possible values:
          • SPOT (String): Simulate under spot measure.
          • TERMINAL (String): Simulate under terminal measure.
        • stateSpace: Possible values:
          • LOGNORMAL (String): Simulate L = exp(Y).
          • NORMAL (String): Simulate L = Y.
        • simulationTimeInterpolationMethod: Possible values:
          • ROUND_DOWN: \( L(S,T;t) \) is mapped to \( L(S,T,t_{j}) \) with \( t_{j} \) being the largest time in the time discretization such that \( t_{j} \leq t \).
          • ROUND_NEAREST: \( L(S,T;t) \) is mapped to \( L(S,T,t_{j}) \) with \( t_{j} \) being the nearest time in the time discretization.
        • liborCap: An optional Double value applied as a cap to the LIBOR rates. May be used to limit the simulated valued to prevent values attaining POSITIVE_INFINITY and numerical problems. To disable the cap, set liborCap to Double.POSITIVE_INFINITY.
        • calibrationParameters: Possible values:
          • Map<String,Object> a parameter map with the following key/value pairs:
            • accuracy: Double specifying the required solver accuracy.
            • maxIterations: Integer specifying the maximum iterations for the solver.
        Parameters:
        liborPeriodDiscretization - The discretization of the interest rate curve into forward rates (tenor structure).
        analyticModel - The associated analytic model of this model (containing the associated market data objects like curve).
        forwardRateCurve - The initial values for the forward rates.
        discountCurve - The discount curve to use. This will create an LMM model with a deterministic zero-spread discounting adjustment.
        randomVariableFactory - The random variable factory used to create the initial values of the model.
        covarianceModel - The covariance model to use.
        calibrationProducts - The vector of calibration items (a union of a product, target value and weight) for the objective function sum weight(i) * (modelValue(i)-targetValue(i).
        properties - Key value map specifying properties like measure and stateSpace.
        Returns:
        A new instance of LIBORMarketModelFromCovarianceModel, possibly calibrated.
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • getReferenceDate

        public LocalDateTime getReferenceDate()
        Description copied from interface: ProcessModel
        Returns the model's date corresponding to the time discretization's \( t = 0 \). Note: Currently not all models provide a reference date. This will change in future versions.
        Specified by:
        getReferenceDate in interface ProcessModel
        Overrides:
        getReferenceDate in class AbstractProcessModel
        Returns:
        The model's date corresponding to the time discretization's \( t = 0 \).
      • getNumeraire

        public RandomVariable getNumeraire​(MonteCarloProcess process,
                                           double time)
                                    throws CalculationException
        Return the numeraire at a given time. The numeraire is provided for interpolated points. If requested on points which are not part of the tenor discretization, the numeraire uses a linear interpolation of the reciprocal value. See ISBN 0470047224 for details.
        Specified by:
        getNumeraire in interface ProcessModel
        Parameters:
        time - Time time t for which the numeraire should be returned N(t).
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        Returns:
        The numeraire at the specified time as RandomVariable
        Throws:
        CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
      • getForwardDiscountBond

        public RandomVariable getForwardDiscountBond​(MonteCarloProcess process,
                                                     double time,
                                                     double maturity)
                                              throws CalculationException
        Description copied from interface: TermStructureModel
        Returns the time \( t \) forward bond derived from the numeraire, i.e., \( P(T;t) = E( \frac{N(t)}{N(T)} \vert \mathcal{F}_{t} ) \). Note: It is guaranteed that the random variabble returned by this method is \( \mathcal{F}_{t} ) \)-measurable.
        Specified by:
        getForwardDiscountBond in interface TermStructureModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        time - The evaluation time.
        maturity - The maturity.
        Returns:
        The forward bond P(T;t).
        Throws:
        CalculationException - Thrown if model fails to calculate the random variable.
      • getInitialState

        public RandomVariable[] getInitialState​(MonteCarloProcess process)
        Description copied from interface: ProcessModel
        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.
        Specified by:
        getInitialState in interface ProcessModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        Returns:
        The initial value of the state variable of the process Y(t=0).
      • getDrift

        public RandomVariable[] 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. The drift will be zero for rates being already fixed. The method currently provides the drift for either Measure.SPOT or Measure.TERMINAL - depending how the model object was constructed. For Measure.TERMINAL the j-th entry of the return value is the random variable \[ \mu_{j}^{\mathbb{Q}^{P(T_{n})}}(t) \ = \ - \mathop{\sum_{l\geq j+1}}_{l\leq n-1} \frac{\delta_{l}}{1+\delta_{l} L_{l}(t)} (\lambda_{j}(t) \cdot \lambda_{l}(t)) \] and for Measure.SPOT the j-th entry of the return value is the random variable \[ \mu_{j}^{\mathbb{Q}^{N}}(t) \ = \ \sum_{m(t) < l\leq j} \frac{\delta_{l}}{1+\delta_{l} L_{l}(t)} (\lambda_{j}(t) \cdot \lambda_{l}(t)) \] where \( \lambda_{j} \) is the vector for factor loadings for the j-th component of the stochastic process (that is, the diffusion part is \( \sum_{k=1}^m \lambda_{j,k} \mathrm{d}W_{k} \)). Note: The scalar product of the factor loadings determines the instantaneous covariance. If the model is written in log-coordinates (using exp as a state space transform), we find \(\lambda_{j} \cdot \lambda_{l} = \sum_{k=1}^m \lambda_{j,k} \lambda_{l,k} = \sigma_{j} \sigma_{l} \rho_{j,l} \). If the model is written without a state space transformation (in its orignial coordinates) then \(\lambda_{j} \cdot \lambda_{l} = \sum_{k=1}^m \lambda_{j,k} \lambda_{l,k} = L_{j} L_{l} \sigma_{j} \sigma_{l} \rho_{j,l} \).
        Specified by:
        getDrift in interface ProcessModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        timeIndex - Time index i for which the drift should be returned μ(ti).
        realizationAtTimeIndex - Time current forward rate vector at time index i which should be used in the calculation.
        realizationPredictor - The given realization at timeIndex+1 or null if no predictor is available.
        Returns:
        The drift vector μ(ti) as RandomVariableFromDoubleArray[]
        See Also:
        The calculation of the drift is consistent with the calculation of the numeraire in getNumeraire., The factor loading \( \lambda_{j,k} \).
      • getFactorLoading

        public RandomVariable[] getFactorLoading​(MonteCarloProcess process,
                                                 int timeIndex,
                                                 int componentIndex,
                                                 RandomVariable[] realizationAtTimeIndex)
        Description copied from interface: ProcessModel
        This method has to be implemented to return the factor loadings, i.e. the coefficient vector
        λj = (λ1,j, ..., λm,j) such that X = f(Y) and
        dYj = μj dt + λ1,j dW1 + ... + λm,j dWm
        in an m-factor model. Here j denotes index of the component of the resulting process.
        Specified by:
        getFactorLoading in interface ProcessModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        timeIndex - The time index (related to the model times discretization).
        componentIndex - The index j of the driven component.
        realizationAtTimeIndex - The realization of X at the time corresponding to timeIndex (in order to implement local and stochastic volatlity models).
        Returns:
        The factor loading for given factor and component.
      • applyStateSpaceTransform

        public RandomVariable applyStateSpaceTransform​(MonteCarloProcess process,
                                                       int timeIndex,
                                                       int componentIndex,
                                                       RandomVariable randomVariable)
        Description copied from interface: ProcessModel
        Applies the state space transform fi to the given state random variable such that Yi → fi(Yi) =: Xi.
        Specified by:
        applyStateSpaceTransform in interface ProcessModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        timeIndex - The time index (related to the model times discretization).
        componentIndex - The component index i.
        randomVariable - The state random variable Yi.
        Returns:
        New random variable holding the result of the state space transformation.
      • applyStateSpaceTransformInverse

        public RandomVariable applyStateSpaceTransformInverse​(MonteCarloProcess process,
                                                              int timeIndex,
                                                              int componentIndex,
                                                              RandomVariable randomVariable)
        Description copied from interface: ProcessModel
        Applies the inverse state space transform f-1i to the given random variable such that Xi → f-1i(Xi) =: Yi.
        Specified by:
        applyStateSpaceTransformInverse in interface ProcessModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        timeIndex - The time index (related to the model times discretization).
        componentIndex - The component index i.
        randomVariable - The state random variable Xi.
        Returns:
        New random variable holding the result of the state space transformation.
      • getRandomVariableForConstant

        public RandomVariable getRandomVariableForConstant​(double value)
        Description copied from interface: ProcessModel
        Return a random variable initialized with a constant using the models random variable factory.
        Specified by:
        getRandomVariableForConstant in interface ProcessModel
        Parameters:
        value - The constant value.
        Returns:
        A new random variable initialized with a constant value.
      • getForwardRate

        public RandomVariable getForwardRate​(MonteCarloProcess process,
                                             double time,
                                             double periodStart,
                                             double periodEnd)
                                      throws CalculationException
        Description copied from interface: TermStructureModel
        Returns the time \( t \) forward rate on the models forward curve. Note: It is guaranteed that the random variable returned by this method is \( \mathcal{F}_{t} ) \)-measurable.
        Specified by:
        getForwardRate in interface TermStructureModel
        Parameters:
        process - The discretization process generating this model. The process provides call backs for TimeDiscretization and allows calls to getProcessValue for timeIndices less or equal the given one.
        time - The evaluation time.
        periodStart - The period start of the forward rate.
        periodEnd - The period end of the forward rate.
        Returns:
        The forward rate.
        Throws:
        CalculationException - Thrown if model fails to calculate the random variable.
      • getNumberOfComponents

        public int getNumberOfComponents()
        Description copied from interface: ProcessModel
        Returns the number of components
        Specified by:
        getNumberOfComponents in interface ProcessModel
        Returns:
        The number of components
      • getNumberOfLibors

        public int getNumberOfLibors()
        Description copied from interface: LIBORModel
        Get the number of LIBORs in the LIBOR discretization.
        Specified by:
        getNumberOfLibors in interface LIBORModel
        Returns:
        The number of LIBORs in the LIBOR discretization
      • getNumberOfFactors

        public int getNumberOfFactors()
        Description copied from interface: ProcessModel
        Returns the number of factors m, i.e., the number of independent Brownian drivers.
        Specified by:
        getNumberOfFactors in interface ProcessModel
        Returns:
        The number of factors.
      • getLiborPeriod

        public double getLiborPeriod​(int timeIndex)
        Description copied from interface: LIBORModel
        The period start corresponding to a given forward rate discretization index.
        Specified by:
        getLiborPeriod in interface LIBORModel
        Parameters:
        timeIndex - The index corresponding to a given time (interpretation is start of period)
        Returns:
        The period start corresponding to a given forward rate discretization index.
      • getLiborPeriodIndex

        public int getLiborPeriodIndex​(double time)
        Description copied from interface: LIBORModel
        Same as java.util.Arrays.binarySearch(liborPeriodDiscretization,time). Will return a negative value if the time is not found, but then -index-1 corresponds to the index of the smallest time greater than the given one.
        Specified by:
        getLiborPeriodIndex in interface LIBORModel
        Parameters:
        time - The period start.
        Returns:
        The index corresponding to a given time (interpretation is start of period)
      • getIntegratedLIBORCovariance

        public double[][][] getIntegratedLIBORCovariance​(TimeDiscretization simulationTimeDiscretization)
        Description copied from interface: LIBORMarketModel
        Returns the integrated instantaneous log-forward rate covariance, i.e., \( \int_{0}^{t_i} \mathrm{d} \log(L_{j}) \mathrm{d} \log(L_{k}) \mathrm{d}t \). The array returned has the parametrization [i][j][k], i.e., integratedLIBORCovariance[timeIndex][componentIndex1][componentIndex2].
        Specified by:
        getIntegratedLIBORCovariance in interface LIBORMarketModel
        Parameters:
        simulationTimeDiscretization - The timeDiscretization used for the integration.
        Returns:
        The integrated instantaneous log-LIBOR covariance.
      • getAnalyticModel

        public AnalyticModel getAnalyticModel()
        Description copied from interface: TermStructureModel
        Return the associated analytic model, a collection of market date object like discount curve, forward curve and volatility surfaces.
        Specified by:
        getAnalyticModel in interface TermStructureModel
        Returns:
        The associated analytic model.
      • getSwaptionMarketData

        public SwaptionMarketData getSwaptionMarketData()
        Return the swaption market data used for calibration (if any, may be null).
        Returns:
        The swaption market data used for calibration (if any, may be null).