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Hybrid Heston Hull-White stochastic process

This class implements a three factor Heston Hull-White model

bug This class was not tested enough to guarantee its functionality... work in progress

Hierarchy

Implements

Index

Constructors

constructor

Properties

Protected _T

_T: Time

Protected _corrEquityShortRate

_corrEquityShortRate: Real

_discretization

_discretization: discretization

Protected _discretization1

_discretization1: Discretization

Protected _endDiscount

_endDiscount: DiscountFactor

Protected _hestonProcess

_hestonProcess: HestonProcess

Protected _hullWhiteModel

_hullWhiteModel: HullWhite

Protected _hullWhiteProcess

_hullWhiteProcess: HullWhiteForwardProcess

_isDisposed

_isDisposed: boolean = false

Protected _maxRho

_maxRho: Real

_observables

_observables: Set<Observable> = new Set()

_observers

_observers: Set<Observer> = new Set()

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

drift1

eta

  • Returns Real

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

  • returns the number of independent factors of the process

    Returns Size

hestonProcess

  • Returns HestonProcess

hullWhiteProcess

init

initialValues

  • initialValues(): Real[]

numeraire

  • Parameters

    Returns DiscountFactor

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

time

  • time(date: Date): Time
  • Parameters

    • date: Date

    Returns Time

update

  • update(): void