Options
All
  • Public
  • Public/Protected
  • All
Menu

Geman-Roncoroni process class

This class describes the Geman-Roncoroni process governed by $$ \begin{array}{rcl} dE(t) &=& \left[ \frac{\partial}{\partial t} \mu(t) +\theta_1 \left(\mu(t)-E(t^-)\right)\right]dt +\sigma dW(t) + h(E(t^-))dJ(t) \ \mu(t)&=& \alpha + \beta t +\gamma \cos(\epsilon+2\pi t) +\delta \cos(\zeta + 4\pi t) \end{array} $$

Hierarchy

Implements

Index

Constructors

constructor

Properties

Private _a

_a: Real

Private _alpha

_alpha: Real

Private _b

_b: Real

Private _beta

_beta: Real

Private _d

_d: Real

Private _delta

_delta: Real

_discretization

_discretization: discretization

Private _eps

_eps: Real

Private _gamma

_gamma: Real

_isDisposed

_isDisposed: boolean = false

Private _k

_k: Real

_observables

_observables: Set<Observable> = new Set()

_observers

_observers: Set<Observer> = new Set()

Private _psi

_psi: Real

Private _sig2

_sig2: Real

Private _tau

_tau: Real

Private _theta1

_theta1: Real

Private _theta2

_theta2: Real

Private _theta3

_theta3: Real

Private _urng

_urng: urng_type

Private _x0

_x0: Real

Private _zeta

_zeta: Real

dispose

dispose: () => void

Type declaration

    • (): void
    • Returns void

isDisposed

isDisposed: boolean

notifyObservers

notifyObservers: () => void

Type declaration

    • (): void
    • Returns void

registerObserver

registerObserver: (o: Observer) => void

Type declaration

registerWith

registerWith: (h: Observable) => void

Type declaration

registerWithObservables

registerWithObservables: (o: Observer) => void

Type declaration

unregisterObserver

unregisterObserver: (o: Observer) => void

Type declaration

unregisterWith

unregisterWith: (h: Observable) => Size

Type declaration

unregisterWithAll

unregisterWithAll: () => void

Type declaration

    • (): void
    • Returns void

Methods

apply1

apply2

  • applies a change to the asset value. By default, it returns $ x + \Delta x $.

    Parameters

    Returns Real

covariance

deepUpdate

  • deepUpdate(): void

diffusion1

diffusion2

drift1

drift2

evolve1

evolve2

evolve3

  • Parameters

    Returns Real

expectation1

expectation2

  • 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.

    Parameters

    Returns Real

factors

  • returns the number of independent factors of the process

    Returns Size

init

initialValues

  • initialValues(): Real[]

size

stdDeviation1

stdDeviation2

time

  • time(d: Date): Time
  • returns the time value corresponding to the given date in the reference system of the stochastic process.

    note As a number of processes might not need this functionality, a default implementation is given which raises an exception.

    Parameters

    • d: Date

    Returns Time

update

  • update(): void

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.

    Parameters

    Returns Real

x0