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Merton-76 jump-diffusion process

Hierarchy

Implements

Index

Constructors

constructor

Properties

Private _blackProcess

_discretization

_discretization: discretization

_isDisposed

_isDisposed: boolean = false

Private _jumpIntensity

_jumpIntensity: Handle<Quote>

Private _logJumpVolatility

_logJumpVolatility: Handle<Quote>

Private _logMeanJump

_logMeanJump: Handle<Quote>

_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

apply2

blackVolatility

covariance

deepUpdate

  • deepUpdate(): void

diffusion1

diffusion2

dividendYield

drift1

drift2

evolve1

evolve2

  • returns the asset value after a time interval $ \Delta t $ according to the given discretization. By default, it returns $$ E(x_0,t_0,\Delta t) + S(x_0,t_0,\Delta t) \cdot \Delta w $$ where $ E $ is the expectation and $ S $ the standard deviation.

    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[]

jumpIntensity

  • Returns Handle<Quote>

logJumpVolatility

  • Returns Handle<Quote>

logMeanJump

  • Returns Handle<Quote>

riskFreeRate

size

stateVariable

  • Returns Handle<Quote>

stdDeviation1

stdDeviation2

  • 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.

    Parameters

    Returns Real

time

  • time(d: Date): 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