java.lang.Object
net.finmath.montecarlo.process.MonteCarloProcessFromProcessModel
net.finmath.montecarlo.process.EulerSchemeFromProcessModel
- All Implemented Interfaces:
Cloneable
,MonteCarloProcess
,Process
public class EulerSchemeFromProcessModel extends MonteCarloProcessFromProcessModel
This class implements some numerical schemes for multi-dimensional multi-factor Ito process.
It features the standard Euler scheme and the standard predictor-corrector Euler scheme
for Y, then applies the state space transform \( X = f(Y) \). For the standard Euler scheme
the process Y is discretized as
\[
Y(t_{i+1}) = Y(t_{i}) + \mu(t_{i}) \Delta t_{i} + \sigma(t_{i}) \Delta W(t_{i}) \text{.}
\]
Hence, using the state space transform, it is possible to create a log-Euler scheme, i.e.,
\[
X(t_{i+1}) = X(t_{i}) \cdot \exp\left( (\mu(t_{i}) - \frac{1}{2} \sigma(t_{i})^2) \Delta t_{i} + \sigma(t_{i}) \Delta W(t_{i}) \right) \text{.}
\]
The dimension is called
numberOfComponents
here. The default for numberOfFactors
is 1.- Version:
- 1.4
- Author:
- Christian Fries
- See Also:
The interface definition contains more details.
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static class
EulerSchemeFromProcessModel.Scheme
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Constructor Summary
Constructors Constructor Description EulerSchemeFromProcessModel(ProcessModel model, IndependentIncrements stochasticDriver)
Create an Euler discretization scheme.EulerSchemeFromProcessModel(ProcessModel model, IndependentIncrements stochasticDriver, EulerSchemeFromProcessModel.Scheme scheme)
Create an Euler discretization scheme. -
Method Summary
Modifier and Type Method Description EulerSchemeFromProcessModel
clone()
Create and return a clone of this process.MonteCarloProcess
getCloneWithModifiedData(Map<String,Object> dataModified)
Returns a clone of this model where the specified properties have been modified.MonteCarloProcess
getCloneWithModifiedModel(ProcessModel model)
Returns a clone of this model where the specified properties have been modified.Object
getCloneWithModifiedSeed(int seed)
RandomVariable
getMonteCarloWeights(int timeIndex)
This method returns the weights of a weighted Monte Carlo method (the probability density).int
getNumberOfFactors()
int
getNumberOfPaths()
RandomVariable
getProcessValue(int timeIndex, int componentIndex)
This method returns the realization of the process at a certain time index.EulerSchemeFromProcessModel.Scheme
getScheme()
IndependentIncrements
getStochasticDriver()
String
toString()
Methods inherited from class net.finmath.montecarlo.process.MonteCarloProcessFromProcessModel
applyStateSpaceTransform, applyStateSpaceTransformInverse, getDrift, getFactorLoading, getInitialState, getModel, getNumberOfComponents, getTime, getTimeDiscretization, getTimeIndex
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Constructor Details
-
EulerSchemeFromProcessModel
public EulerSchemeFromProcessModel(ProcessModel model, IndependentIncrements stochasticDriver, EulerSchemeFromProcessModel.Scheme scheme)Create an Euler discretization scheme.- Parameters:
model
- The model (the SDE specifcation) used to generate the (sampling of the) stochastic process.stochasticDriver
- The stochastic driver of the process (e.g. a Brownian motion).scheme
- The scheme to use. SeeEulerSchemeFromProcessModel.Scheme
.
-
EulerSchemeFromProcessModel
Create an Euler discretization scheme.- Parameters:
model
- The model (the SDE specifcation) used to generate the (sampling of the) stochastic process.stochasticDriver
- The stochastic driver of the process (e.g. a Brownian motion).
-
-
Method Details
-
getProcessValue
This method returns the realization of the process at a certain time index.- Parameters:
timeIndex
- Time index at which the process should be observedcomponentIndex
- Component index of the process.- Returns:
- A vector of process realizations (on path)
-
getMonteCarloWeights
This method returns the weights of a weighted Monte Carlo method (the probability density).- Parameters:
timeIndex
- Time index at which the process should be observed- Returns:
- A vector of positive weights
-
getNumberOfPaths
public int getNumberOfPaths()- Returns:
- Returns the numberOfPaths.
-
getNumberOfFactors
public int getNumberOfFactors()- Returns:
- Returns the numberOfFactors.
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getStochasticDriver
- Returns:
- Returns the independent increments interface used in the generation of the process
-
getScheme
- Returns:
- Returns the scheme.
-
clone
Description copied from interface:MonteCarloProcess
Create and return a clone of this process. The clone is not tied to any model, but has the same process specification, that is, if the model is the same, it would generate the same paths.- Specified by:
clone
in interfaceMonteCarloProcess
- Specified by:
clone
in interfaceProcess
- Specified by:
clone
in classMonteCarloProcessFromProcessModel
- Returns:
- Clone of the process
-
getCloneWithModifiedModel
Description copied from interface:MonteCarloProcess
Returns a clone of this model where the specified properties have been modified. Note that there is no guarantee that a model reacts on a specification of a properties in the parameter mapdataModified
. If data is provided which is ignored by the model no exception may be thrown.- Parameters:
model
- The model to be used.- Returns:
- A clone of this model (or this model if no parameter was modified).
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getCloneWithModifiedData
Description copied from interface:MonteCarloProcess
Returns a clone of this model where the specified properties have been modified. Note that there is no guarantee that a model reacts on a specification of a properties in the parameter mapdataModified
. If data is provided which is ignored by the model no exception may be thrown.- Parameters:
dataModified
- Key-value-map of parameters to modify.- Returns:
- A clone of this model (or this model if no parameter was modified).
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getCloneWithModifiedSeed
- Specified by:
getCloneWithModifiedSeed
in classMonteCarloProcessFromProcessModel
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toString
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