Module net.finmath.lib
Class HullWhiteModelWithDirectSimulation
java.lang.Object
net.finmath.montecarlo.model.AbstractProcessModel
net.finmath.montecarlo.interestrate.models.HullWhiteModelWithDirectSimulation
- All Implemented Interfaces:
IndependentModelParameterProvider
,LIBORModel
,TermStructureModel
,ProcessModel
Implements a Hull-White model with time dependent mean reversion speed and time dependent short rate volatility.
Note: This implementation is for illustrative purposes.
For a numerically equivalent, more efficient implementation see
HullWhiteModel
.
Please use HullWhiteModel
for real applications.
Model Dynamics
The Hull-While model assumes the following dynamic for the short rate: \[ d r(t) = ( \theta(t) - a(t) r(t) ) d t + \sigma(t) d W(t) \text{,} \quad r(t_{0}) = r_{0} \text{,} \] where the function \( \theta \) determines the calibration to the initial forward curve, \( a \) is the mean reversion and \( \sigma \) is the instantaneous volatility. The dynamic above is under the equivalent martingale measure corresponding to the numeraire \[ N(t) = \exp\left( \int_0^t r(\tau) \mathrm{d}\tau \right) \text{.} \] The main task of this class is to provide the risk-neutral drift and the volatility to the numerical scheme (given the volatility model), simulating \( r(t_{i}) \). The class then also provides and the corresponding numeraire and forward rates (LIBORs).Time Discrete Model
Assuming piecewise constant coefficients (mean reversion speed \( a \) and short rate volatility \( \sigma \) the class specifies the drift and factor loadings as piecewise constant functions for an Euler-scheme. The class provides the exact Euler step for the short rate r. More specifically (assuming a constant mean reversion speed \( a \) for a moment), considering \[ \Delta \bar{r}(t_{i}) = \frac{1}{t_{i+1}-t_{i}} \int_{t_{i}}^{t_{i+1}} d r(t) \] we find from \[ \exp(-a t) \ \left( \mathrm{d} \left( \exp(a t) r(t) \right) \right) \ = \ a r(t) + \mathrm{d} r(t) \ = \ \theta(t) \mathrm{d}t + \sigma(t) \mathrm{d}W(t) \] that \[ \exp(a t_{i+1}) r(t_{i+1}) - \exp(a t_{i}) r(t_{i}) \ = \ \int_{t_{i}}^{t_{i+1}} \left[ \exp(a t) \theta(t) \mathrm{d}t + \exp(a t) \sigma(t) \mathrm{d}W(t) \right] \] that is \[ r(t_{i+1}) - r(t_{i}) \ = \ -(1-\exp(-a (t_{i+1}-t_{i})) r(t_{i}) + \int_{t_{i}}^{t_{i+1}} \left[ \exp(-a (t_{i+1}-t)) \theta(t) \mathrm{d}t + \exp(-a (t_{i+1}-t)) \sigma(t) \mathrm{d}W(t) \right] \] Assuming piecewise constant \( \sigma \) and \( \theta \), being constant over \( (t_{i},t_{i}+\Delta t_{i}) \), we thus find \[ r(t_{i+1}) - r(t_{i}) \ = \ \frac{1-\exp(-a \Delta t_{i})}{a \Delta t_{i}} \left( ( \theta(t_{i}) - a \bar{r}(t_{i})) \Delta t_{i} \right) + \sqrt{\frac{1-\exp(-2 a \Delta t_{i})}{2 a \Delta t_{i}}} \sigma(t_{i}) \Delta W(t_{i}) \] . In other words, the Euler scheme is exact if the mean reversion \( a \) is replaced by the effective mean reversion \( \frac{1-\exp(-a \Delta t_{i})}{a \Delta t_{i}} a \) and the volatility is replaced by the effective volatility \( \sqrt{\frac{1-\exp(-2 a \Delta t_{i})}{2 a \Delta t_{i}}} \sigma(t_{i}) \). In the calculations above the mean reversion speed is treated as a constants, but it is straight forward to see that the same holds for piecewise constant mean reversion speeds, replacing the expression \( a \ t \) by \( \int_{0}^t a(s) \mathrm{d}s \).Calibration
The drift of the short rate is calibrated to the given forward curve using \[ \theta(t) = \frac{\partial}{\partial T} f(0,t) + a(t) f(0,t) + \phi(t) \text{,} \] where the function \( f \) denotes the instantanenous forward rate and \( \phi(t) = \frac{1}{2} a \sigma^{2}(t) B(t)^{2} + \sigma^{2}(t) B(t) \frac{\partial}{\partial t} B(t) \) with \( B(t) = \frac{1-\exp(-a t)}{a} \).Volatility Model
The Hull-White model is essentially equivalent to LIBOR Market Model where the forward rate normal volatility \( \sigma(t,T) \) is given by \[ \sigma(t,T_{i}) \ = \ (1 + L_{i}(t) (T_{i+1}-T_{i})) \sigma(t) \exp(-a (T_{i}-t)) \frac{1-\exp(-a (T_{i+1}-T_{i}))}{a (T_{i+1}-T_{i})} \] (where \( \{ T_{i} \} \) is the forward rates tenor time discretization (note that this is the normal volatility, not the log-normal volatility). Hence, we interpret both, short rate mean reversion speed and short rate volatility as part of the volatility model. The mean reversion speed and the short rate volatility have to be provided to this class via an object implementingShortRateVolatilityModel
.- Version:
- 1.2
- Author:
- Christian Fries
- See Also:
ShortRateVolatilityModel
,HullWhiteModel
-
Constructor Summary
ConstructorsConstructorDescriptionHullWhiteModelWithDirectSimulation(TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, ShortRateVolatilityModel volatilityModel, Map<String,?> properties)
Creates a Hull-White model which implementsLIBORMarketModel
. -
Method Summary
Modifier and TypeMethodDescriptionapplyStateSpaceTransform(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.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.Return the associated analytic model, a collection of market date object like discount curve, forward curve and volatility surfaces.getCloneWithModifiedData(Map<String,Object> dataModified)
Create a new object implementing LIBORModel, using the new data.Return the discount curve associated the forwards.getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)
This method has to be implemented to return the drift, i.e.getFactorLoading(MonteCarloProcess process, int timeIndex, int componentIndex, RandomVariable[] realizationAtTimeIndex)
This method has to be implemented to return the factor loadings, i.e.getForwardRate(MonteCarloProcess process, double time, double periodStart, double periodEnd)
Returns the time \( t \) forward rate on the models forward curve.Return the initial forward rate curve.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.double
getIntegratedBondSquaredVolatility(double time, double maturity)
getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex)
Return the forward rate at a given timeIndex and for a given liborIndex.double
getLiborPeriod(int timeIndex)
The period start corresponding to a given forward rate discretization index.The tenor time discretization of the forward rate curve.int
getLiborPeriodIndex(double time)
Same as java.util.Arrays.binarySearch(liborPeriodDiscretization,time).Returns a map of independent model parameters of this model.int
Returns the number of componentsint
Returns the number of factors m, i.e., the number of independent Brownian drivers.int
Get the number of LIBORs in the LIBOR discretization.getNumeraire(MonteCarloProcess process, double time)
Return the numeraire at a given time index.getRandomVariableForConstant(double value)
Return a random variable initialized with a constant using the models random variable factory.double
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.Methods inherited from class net.finmath.montecarlo.model.AbstractProcessModel
getInitialValue, getReferenceDate
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface net.finmath.montecarlo.model.ProcessModel
getReferenceDate
Methods inherited from interface net.finmath.montecarlo.interestrate.TermStructureModel
getForwardDiscountBond, getLIBOR
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Constructor Details
-
HullWhiteModelWithDirectSimulation
public HullWhiteModelWithDirectSimulation(TimeDiscretization liborPeriodDiscretization, AnalyticModel analyticModel, ForwardCurve forwardRateCurve, DiscountCurve discountCurve, ShortRateVolatilityModel volatilityModel, Map<String,?> properties)Creates a Hull-White model which implementsLIBORMarketModel
.- Parameters:
liborPeriodDiscretization
- The forward rate discretization to be used in thegetLIBOR
method.analyticModel
- The analytic model to be used (currently not used, may be null).forwardRateCurve
- The forward curve to be used (currently not used, - the model uses disocuntCurve only.discountCurve
- The disocuntCurve (currently also used to determine the forward curve).volatilityModel
- The volatility model specifying mean reversion and instantaneous volatility of the short rate.properties
- A map specifying model properties (currently not used, may be null).
-
-
Method Details
-
getNumberOfComponents
public int getNumberOfComponents()Description copied from interface:ProcessModel
Returns the number of components- Specified by:
getNumberOfComponents
in interfaceProcessModel
- Returns:
- The number of components
-
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 interfaceProcessModel
- Returns:
- The number of factors.
-
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 interfaceProcessModel
- 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 interfaceProcessModel
- 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.
-
getInitialState
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 interfaceProcessModel
- 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).
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getNumeraire
public RandomVariable getNumeraire(MonteCarloProcess process, double time) throws CalculationExceptionDescription copied from interface:ProcessModel
Return the numeraire at a given time index. Note: The random variable returned is a defensive copy and may be modified.- Specified by:
getNumeraire
in interfaceProcessModel
- 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 time t for which the numeraire N(t) should be returned.- Returns:
- The numeraire at the specified time as
RandomVariable
- Throws:
CalculationException
- Thrown if the valuation fails, specific cause may be available via thecause()
method.
-
getDrift
public RandomVariable[] getDrift(MonteCarloProcess process, int timeIndex, RandomVariable[] realizationAtTimeIndex, RandomVariable[] realizationPredictor)Description copied from interface:ProcessModel
This method has to be implemented to return the drift, i.e. the coefficient vector
μ = (μ1, ..., μn) 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. Since the model is provided only on a time discretization, the method may also (should try to) return the drift as \( \frac{1}{t_{i+1}-t_{i}} \int_{t_{i}}^{t_{i+1}} \mu(\tau) \mathrm{d}\tau \).- Specified by:
getDrift
in interfaceProcessModel
- 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).realizationAtTimeIndex
- The given realization at timeIndexrealizationPredictor
- The given realization attimeIndex+1
or null if no predictor is available.- Returns:
- The drift or average drift from timeIndex to timeIndex+1, i.e. \( \frac{1}{t_{i+1}-t_{i}} \int_{t_{i}}^{t_{i+1}} \mu(\tau) \mathrm{d}\tau \) (or a suitable approximation).
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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 interfaceProcessModel
- 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.
-
getRandomVariableForConstant
Description copied from interface:ProcessModel
Return a random variable initialized with a constant using the models random variable factory.- Specified by:
getRandomVariableForConstant
in interfaceProcessModel
- 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 CalculationExceptionDescription 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 interfaceTermStructureModel
- 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.
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getLIBOR
public RandomVariable getLIBOR(MonteCarloProcess process, int timeIndex, int liborIndex) throws CalculationExceptionDescription copied from interface:LIBORModel
Return the forward rate at a given timeIndex and for a given liborIndex.- Specified by:
getLIBOR
in interfaceLIBORModel
- 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 (associated withProcess.getTimeDiscretization()
.liborIndex
- The forward rate index (associated withLIBORModel.getLiborPeriodDiscretization()
.- Returns:
- The forward rate.
- Throws:
CalculationException
- Thrown if calculation failed.
-
getLiborPeriodDiscretization
Description copied from interface:LIBORModel
The tenor time discretization of the forward rate curve.- Specified by:
getLiborPeriodDiscretization
in interfaceLIBORModel
- Returns:
- The tenor time discretization of the forward rate curve.
-
getNumberOfLibors
public int getNumberOfLibors()Description copied from interface:LIBORModel
Get the number of LIBORs in the LIBOR discretization.- Specified by:
getNumberOfLibors
in interfaceLIBORModel
- Returns:
- The number of LIBORs in the LIBOR discretization
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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 interfaceLIBORModel
- 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 interfaceLIBORModel
- Parameters:
time
- The period start.- Returns:
- The index corresponding to a given time (interpretation is start of period)
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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 interfaceTermStructureModel
- Returns:
- The associated analytic model.
-
getDiscountCurve
Description copied from interface:TermStructureModel
Return the discount curve associated the forwards.- Specified by:
getDiscountCurve
in interfaceTermStructureModel
- Returns:
- the discount curve associated the forwards.
-
getForwardRateCurve
Description copied from interface:TermStructureModel
Return the initial forward rate curve.- Specified by:
getForwardRateCurve
in interfaceTermStructureModel
- Returns:
- the forward rate curve
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getCloneWithModifiedData
Description copied from interface:LIBORModel
Create a new object implementing LIBORModel, using the new data.- Specified by:
getCloneWithModifiedData
in interfaceLIBORModel
- Specified by:
getCloneWithModifiedData
in interfaceProcessModel
- Specified by:
getCloneWithModifiedData
in interfaceTermStructureModel
- Parameters:
dataModified
- A map with values to be used in constructions (keys are identical to parameter names of the constructors).- Returns:
- A new object implementing LIBORModel, using the new data.
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getShortRateConditionalVariance
public double 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.- Parameters:
time
- The parameter s in \( \int_{s}^{t} \sigma^{2}(\tau) \exp(-2 \cdot \int_{\tau}^{t} a(u) \mathrm{d}u ) \ \mathrm{d}\tau \)maturity
- The parameter t in \( \int_{s}^{t} \sigma^{2}(\tau) \exp(-2 \cdot \int_{\tau}^{t} a(u) \mathrm{d}u ) \ \mathrm{d}\tau \)- Returns:
- The conditional variance of the short rate, \( \mathop{Var}(r(t) \vert r(s) ) \).
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getIntegratedBondSquaredVolatility
public double getIntegratedBondSquaredVolatility(double time, double maturity) -
getModelParameters
Description copied from interface:IndependentModelParameterProvider
Returns a map of independent model parameters of this model.- Specified by:
getModelParameters
in interfaceIndependentModelParameterProvider
- Returns:
- Map of independent model parameters of this model.
-