Hull-White stochastic process. More...
#include <ql/processes/hullwhiteprocess.hpp>
Public Member Functions | |
HullWhiteProcess (const Handle< YieldTermStructure > &h, Real a, Real sigma) | |
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virtual Real | evolve (Time t0, Real x0, Time dt, Real dw) const |
virtual Real | apply (Real x0, Real dx) const |
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virtual Size | factors () const |
returns the number of independent factors of the process | |
virtual Time | time (const Date &) const |
void | update () |
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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 () |
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Observable (const Observable &) | |
Observable & | operator= (const Observable &) |
void | notifyObservers () |
StochasticProcess1D interface | |
ext::shared_ptr< QuantLib::OrnsteinUhlenbeckProcess > | process_ |
Handle< YieldTermStructure > | h_ |
Real | a_ |
Real | sigma_ |
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 |
Real | a () const |
Real | sigma () const |
Real | alpha (Time t) const |
Additional Inherited Members | |
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typedef boost::unordered_set< ext::shared_ptr< Observable > > | set_type |
typedef set_type::iterator | iterator |
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StochasticProcess1D () | |
StochasticProcess1D (const ext::shared_ptr< discretization > &) | |
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StochasticProcess () | |
StochasticProcess (const ext::shared_ptr< discretization > &) | |
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ext::shared_ptr< discretization > | discretization_ |
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ext::shared_ptr< discretization > | discretization_ |
Hull-White stochastic process.
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.
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.
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.