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Hierarchy

Implements

Index

Constructors

constructor

Properties

_discretization

_discretization: discretization

Private _hestonProcess

_hestonProcess: HestonProcess

_isDisposed

_isDisposed: boolean = false

Private _kappa

_kappa: Real

Private _leverageFct

_leverageFct: LocalVolTermStructure

_observables

_observables: Set<Observable> = new Set()

_observers

_observers: Set<Observer> = new Set()

Private _rho

_rho: Real

Private _sigma

_sigma: Real

Private _theta

_theta: Real

Private _v0

_v0: 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

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.

    Parameters

    Returns Matrix

deepUpdate

  • deepUpdate(): void

diffusion1

dividendYield

drift1

evolve1

expectation1

  • 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.

    Parameters

    Returns Real[]

factors

init

initialValues

  • initialValues(): Real[]

kappa

  • Returns Real

leverageFct

rho

  • Returns Real

riskFreeRate

s0

  • Returns Handle<Quote>

sigma

  • Returns Real

size

stdDeviation1

  • 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.

    Parameters

    Returns Matrix

theta

  • Returns Real

time

  • time(d: Date): Time
  • Parameters

    • d: Date

    Returns Time

update

  • update(): void

v0

  • Returns Real