Forward G2 stochastic process More...
#include <ql/processes/g2process.hpp>
Public Member Functions | |
| G2ForwardProcess (Real a, Real sigma, Real b, Real eta, Real rho) | |
| Public Member Functions inherited from ForwardMeasureProcess | |
| virtual void | setForwardMeasureTime (Time) |
| Time | getForwardMeasureTime () const |
| Public Member Functions inherited from StochasticProcess | |
| virtual Size | factors () const |
| returns the number of independent factors of the process | |
| virtual Array | evolve (Time t0, const Array &x0, Time dt, const Array &dw) const |
| virtual Array | apply (const Array &x0, const Array &dx) const |
| virtual Time | time (const Date &) const |
| void | update () override |
| Public Member Functions inherited from Observer | |
| Observer (const Observer &) | |
| Observer & | operator= (const Observer &) |
| std::pair< iterator, bool > | registerWith (const ext::shared_ptr< Observable > &) |
| void | registerWithObservables (const ext::shared_ptr< Observer > &) |
| Size | unregisterWith (const ext::shared_ptr< Observable > &) |
| void | unregisterWithAll () |
| virtual void | deepUpdate () |
| Public Member Functions inherited from Observable | |
| Observable (const Observable &) | |
| Observable & | operator= (const Observable &) |
| Observable (Observable &&)=delete | |
| Observable & | operator= (Observable &&)=delete |
| void | notifyObservers () |
StochasticProcess interface | |
| Real | x0_ = 0.0 |
| Real | y0_ = 0.0 |
| Real | a_ |
| Real | sigma_ |
| Real | b_ |
| Real | eta_ |
| Real | rho_ |
| ext::shared_ptr< QuantLib::OrnsteinUhlenbeckProcess > | xProcess_ |
| ext::shared_ptr< QuantLib::OrnsteinUhlenbeckProcess > | yProcess_ |
| Size | size () const override |
| returns the number of dimensions of the stochastic process | |
| Array | initialValues () const override |
| returns the initial values of the state variables | |
| Array | drift (Time t, const Array &x) const override |
| returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \) | |
| Matrix | diffusion (Time t, const Array &x) const override |
| returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \) | |
| Array | expectation (Time t0, const Array &x0, Time dt) const override |
| Matrix | stdDeviation (Time t0, const Array &x0, Time dt) const override |
| Matrix | covariance (Time t0, const Array &x0, Time dt) const override |
| Real | xForwardDrift (Time t, Time T) const |
| Real | yForwardDrift (Time t, Time T) const |
| Real | Mx_T (Real s, Real t, Real T) const |
| Real | My_T (Real s, Real t, Real T) const |
Additional Inherited Members | |
| Public Types inherited from Observer | |
| typedef set_type::iterator | iterator |
| Protected Member Functions inherited from ForwardMeasureProcess | |
| ForwardMeasureProcess (Time T) | |
| ForwardMeasureProcess (const ext::shared_ptr< discretization > &) | |
| StochasticProcess (ext::shared_ptr< discretization >) | |
| Protected Attributes inherited from ForwardMeasureProcess | |
| Time | T_ |
| ext::shared_ptr< discretization > | discretization_ |
Detailed Description
Forward G2 stochastic process
Member Function Documentation
◆ size()
|
overridevirtual |
returns the number of dimensions of the stochastic process
Implements StochasticProcess.
◆ initialValues()
|
overridevirtual |
returns the initial values of the state variables
Implements StochasticProcess.
◆ drift()
returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \)
Implements StochasticProcess.
◆ diffusion()
returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \)
Implements StochasticProcess.
◆ expectation()
returns the expectation \( E(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) 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 StochasticProcess.
◆ stdDeviation()
returns the standard deviation \( S(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) 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 StochasticProcess.
◆ covariance()
returns the covariance \( V(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) 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 StochasticProcess.
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