MfStateProcess Class Reference

Markov functional state process class. More...

#include <ql/experimental/models/mfstateprocess.hpp>

Inheritance diagram for MfStateProcess:

Public Member Functions

 MfStateProcess (double reversion, const Array &times, const Array &vols)
 
StochasticProcess interface
Real x0 () const
 returns the initial value of the state variable
 
Real drift (Time t, Real x) const
 returns the drift part of the equation, i.e. $ \mu(t, x_t) $
 
Real diffusion (Time t, Real x) const
 returns the diffusion part of the equation, i.e. $ \sigma(t, x_t) $
 
Real expectation (Time t0, Real x0, Time dt) const
 
Real stdDeviation (Time t0, Real x0, Time dt) const
 
Real variance (Time t0, Real x0, Time dt) const
 
- Public Member Functions inherited from StochasticProcess1D
virtual Real evolve (Time t0, Real x0, Time dt, Real dw) const
 
virtual Real apply (Real x0, Real dx) const
 
- Public Member Functions inherited from StochasticProcess
virtual Size factors () const
 returns the number of independent factors of the process
 
virtual Time time (const Date &) const
 
void update ()
 
- Public Member Functions inherited from Observer
 Observer (const Observer &)
 
Observeroperator= (const Observer &)
 
std::pair< std::set
< boost::shared_ptr
< Observable > >::iterator,
bool > 
registerWith (const boost::shared_ptr< Observable > &)
 
Size unregisterWith (const boost::shared_ptr< Observable > &)
 
void unregisterWithAll ()
 
- Public Member Functions inherited from Observable
 Observable (const Observable &)
 
Observableoperator= (const Observable &)
 
void notifyObservers ()
 

Additional Inherited Members

- Protected Member Functions inherited from StochasticProcess1D
 StochasticProcess1D (const boost::shared_ptr< discretization > &)
 
- Protected Member Functions inherited from StochasticProcess
 StochasticProcess (const boost::shared_ptr< discretization > &)
 
- Protected Attributes inherited from StochasticProcess1D
boost::shared_ptr< discretizationdiscretization_
 
- Protected Attributes inherited from StochasticProcess
boost::shared_ptr< discretizationdiscretization_
 

Detailed Description

Markov functional state process class.

This class describes the process governed by

\[ dx = \sigma(t) e^{at} dW(t) \]

Member Function Documentation

Real expectation ( Time  t0,
Real  x0,
Time  dt 
) const
virtual

returns the expectation $ E(x_{t_0 + \Delta t} | x_{t_0} = x_0) $ of the process after a time interval $ \Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess1D.

Real stdDeviation ( Time  t0,
Real  x0,
Time  dt 
) const
virtual

returns the standard deviation $ S(x_{t_0 + \Delta t} | x_{t_0} = x_0) $ of the process after a time interval $ \Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess1D.

Real variance ( Time  t0,
Real  x0,
Time  dt 
) const
virtual

returns the variance $ V(x_{t_0 + \Delta t} | x_{t_0} = x_0) $ of the process after a time interval $ \Delta t $ according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess1D.