Markov functional state process class. More...
#include <mfstateprocess.hpp>
Inheritance diagram for MfStateProcess:
Collaboration diagram for MfStateProcess:
Public Member Functions | |
| MfStateProcess (Real reversion, const Array ×, const Array &vols) | |
| 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 | |
| ~StochasticProcess () override=default | |
| virtual Size | factors () const |
| returns the number of independent factors of the process More... | |
| virtual Time | time (const Date &) const |
| void | update () override |
| Public Member Functions inherited from Observer | |
| Observer ()=default | |
| Observer (const Observer &) | |
| Observer & | operator= (const Observer &) |
| virtual | ~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 | update ()=0 |
| virtual void | deepUpdate () |
| Public Member Functions inherited from Observable | |
| Observable ()=default | |
| Observable (const Observable &) | |
| Observable & | operator= (const Observable &) |
| Observable (Observable &&)=delete | |
| Observable & | operator= (Observable &&)=delete |
| virtual | ~Observable ()=default |
| void | notifyObservers () |
StochasticProcess interface | |
| Real | reversion_ |
| bool | reversionZero_ = false |
| const Array & | times_ |
| const Array & | vols_ |
| Real | x0 () const override |
| returns the initial value of the state variable More... | |
| Real | drift (Time t, Real x) const override |
| returns the drift part of the equation, i.e. \( \mu(t, x_t) \) More... | |
| Real | diffusion (Time t, Real x) const override |
| returns the diffusion part of the equation, i.e. \( \sigma(t, x_t) \) More... | |
| Real | expectation (Time t0, Real x0, Time dt) const override |
| Real | stdDeviation (Time t0, Real x0, Time dt) const override |
| Real | variance (Time t0, Real x0, Time dt) const override |
Additional Inherited Members | |
| Public Types inherited from Observer | |
| typedef set_type::iterator | iterator |
| Protected Member Functions inherited from StochasticProcess1D | |
| StochasticProcess1D ()=default | |
| StochasticProcess1D (ext::shared_ptr< discretization >) | |
| Protected Member Functions inherited from StochasticProcess | |
| StochasticProcess ()=default | |
| StochasticProcess (ext::shared_ptr< discretization >) | |
| Protected Attributes inherited from StochasticProcess1D | |
| ext::shared_ptr< discretization > | discretization_ |
| Protected Attributes inherited from StochasticProcess | |
| ext::shared_ptr< discretization > | discretization_ |
Detailed Description
Markov functional state process class.
This class describes the process governed by
\[ dx = \sigma(t) e^{at} dW(t) \]
Definition at line 36 of file mfstateprocess.hpp.
Constructor & Destructor Documentation
◆ MfStateProcess()
| MfStateProcess | ( | Real | reversion, |
| const Array & | times, | ||
| const Array & | vols | ||
| ) |
Member Function Documentation
◆ x0()
|
overridevirtual |
returns the initial value of the state variable
Implements StochasticProcess1D.
Definition at line 42 of file mfstateprocess.cpp.
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◆ drift()
returns the drift part of the equation, i.e. \( \mu(t, x_t) \)
Implements StochasticProcess1D.
Definition at line 44 of file mfstateprocess.cpp.
◆ diffusion()
returns the diffusion part of the equation, i.e. \( \sigma(t, x_t) \)
Implements StochasticProcess1D.
Definition at line 46 of file mfstateprocess.cpp.
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◆ expectation()
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.
Definition at line 52 of file mfstateprocess.cpp.
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◆ stdDeviation()
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.
Definition at line 56 of file mfstateprocess.cpp.
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◆ variance()
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.
Definition at line 60 of file mfstateprocess.cpp.
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Member Data Documentation
◆ reversion_
|
private |
Definition at line 50 of file mfstateprocess.hpp.
◆ reversionZero_
|
private |
Definition at line 51 of file mfstateprocess.hpp.
◆ times_
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private |
Definition at line 52 of file mfstateprocess.hpp.
◆ vols_
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private |
Definition at line 53 of file mfstateprocess.hpp.