Module net.finmath.lib
Package net.finmath.montecarlo.process
Interfaced for stochastic processes and numerical schemes for stochastic processes (SDEs), like the Euler scheme.
The Euler scheme implementation is more generic and can be configured for
logEuler scheme or predictor corrector scheme.
The parameters have to be provided by a process model.
 Author:
 Christian Fries
 See Also:
net.finmath.montecarlo.model

Interface Summary Interface Description MonteCarloProcess The interface for a process (numerical scheme) of a stochastic process X where X = f(Y) and Y is an ItÃ´ process
\[ dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m} \] The parameters are provided by a model implementingProcessModel
: The value of Y(0) is provided by the methodProcessModel.getInitialState(net.finmath.montecarlo.process.MonteCarloProcess)
.Process The interface for a stochastic process X.ProcessTimeDiscretizationProvider An object implementing this interfaces provides a suggestion for an optimal timediscretization associated with this object. 
Class Summary Class Description EulerSchemeFromProcessModel This class implements some numerical schemes for multidimensional multifactor Ito process.LinearInterpolatedTimeDiscreteProcess A linear interpolated time discrete process, that is, given a collection of tuples (Double
,RandomVariable
) representing realizations \( X(t_{i}) \) this class implements theProcess
and creates a stochastic process \( t \mapsto X(t) \) where \[ X(t) = \frac{t_{i+1}  t}{t_{i+1}t_{i}} X(t_{i}) + \frac{t  t_{i}}{t_{i+1}t_{i}} X(t_{i+1}) \] with \( t_{i} \leq t \leq t_{i+1} \).MonteCarloProcessFromProcessModel This class is an abstract base class to implement a multidimensional multifactor Ito process. 
Enum Summary Enum Description EulerSchemeFromProcessModel.Scheme