HullWhiteForwardProcess Class Reference
[Stochastic processes]
Forward Hull-White stochastic process
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#include <ql/processes/hullwhiteprocess.hpp>

Public Member Functions | |
| HullWhiteForwardProcess (const Handle< YieldTermStructure > &h, Real a, Real sigma) | |
| Real | a () const |
| Real | sigma () const |
| Real | alpha (Time t) const |
| Real | M_T (Real s, Real t, Real T) const |
| Real | B (Time t, Time T) const |
StochasticProcess1D 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. | |
| Real | diffusion (Time t, Real x) const |
returns the diffusion part of the equation, i.e. | |
| 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 |
Protected Attributes | |
|
boost::shared_ptr < QuantLib::OrnsteinUhlenbeckProcess > | process_ |
| Handle< YieldTermStructure > | h_ |
| Real | a_ |
| Real | sigma_ |
Detailed Description
Forward Hull-White stochastic process
Member Function Documentation
| Real expectation | ( | Time | t0, | |
| Real | x0, | |||
| Time | dt | |||
| ) | const [virtual] |
returns the expectation
of the process after a time interval
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
of the process after a time interval
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
of the process after a time interval
according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.
Reimplemented from StochasticProcess1D.