Maple für Professional
Maple für Akademiker
Maple für Studenten
Maple Personal Edition
Maple Player
Maple Player für iPad
MapleSim für Professional
MapleSim für Akademiker
Maple T.A. - Testen & beurteilen
Maple T.A. MAA Placement Test Suite
Möbius - Online-Courseware
Machine Design / Industrial Automation
Luft- und Raumfahrt
Fahrzeugtechnik
Robotics
Energiebranche
System Simulation and Analysis
Model development for HIL
Anlagenmodelle für den Regelungsentwurf
Robotics/Motion Control/Mechatronics
Other Application Areas
Mathematikausbildung
Technik
Allgemein- und berufsbildende Schulen
Testen und beurteilen
Studierende
Finanzmodelle
Betriebsforschung
Hochleistungsrechnen
Physik
Live-Webinare
Aufgezeichnete Webinare
Geplante Veranstaltungen
MaplePrimes
Maplesoft-Blog
Maplesoft-Mitgliedschaft
Maple Ambassador Program
MapleCloud
Technische Whitepapers
E-Mail Newsletters
Maple-Bücher
Math Matters
Anwendungs-Center
MapleSim Modell-Galerie
Anwenderberichte
Exploring Engineering Fundamentals
Lehrkonzepte mit Maple
Maplesoft Welcome-Center
Resource-Center für Lehrer
Help-Center für Studierende
Finance[MertonJumpDiffusion] - create new jump diffusion process
Calling Sequence
MertonJumpDiffusion(X, lambda, a, b)
MertonJumpDiffusion(, sigma, r, d, lambda, a, b, t, S)
Parameters
X
-
Black-Scholes process
lambda
intensity of the lognormal Poisson process
a
scale parameter of the lognormal Poisson process
b
shape parameter of the lognormal Poisson process
non-negative constant; initial value
sigma
non-negative constant, procedure, or local volatility structure; volatility
r
non-negative constant, procedure, or yield term structure; risk-free rate
d
non-negative constant, procedure, or yield term structure; dividend yield
t
name; time variable
S
name; state variable
Description
The MertonJumpDiffusion command creates a new jump diffusion process that is governed by the stochastic differential equation (SDE)
where
is the drift parameter
is the volatility parameter
is the standard Wiener process
and
is a compound Poisson process of the form
such that is independent and lognormally distributed with mean and standard deviation .
Both the drift parameter mu and the volatility parameter sigma can be either constant or time-dependent. In the second case they can be specified either as an algebraic expression containing one indeterminate, or as a procedure that accepts one parameter (the time) and returns the corresponding value of the drift (volatility).
Similar to the drift and the volatility parameters, the intensity parameter lambda can be either constant or time-dependent. In the second case it can be specified either as an algebraic expression containing one indeterminate or as a procedure that accepts one parameter (the time).
Both the scale parameter a and the shape parameter b of the underlying lognormal Poisson process must be real constants.
Compatibility
The Finance[MertonJumpDiffusion] command was introduced in Maple 15.
For more information on Maple 15 changes, see Updates in Maple 15.
Examples
First consider two examples of jump diffusion with low volatility to observe the effect of jumps.
Now consider similar processes but with relatively high volatility.
Here is another way to define the same jump diffusion process.
See Also
Finance[BlackScholesProcess], Finance[BrownianMotion], Finance[Diffusion], Finance[Drift], Finance[ExpectedValue], Finance[ForwardCurve], Finance[GeometricBrownianMotion], Finance[ImpliedVolatility], Finance[ItoProcess], Finance[LocalVolatility], Finance[LocalVolatilitySurface], Finance[PathPlot], Finance[SamplePath], Finance[SampleValues], Finance[StochasticProcesses], Finance[SVJJProcess]
References
Glasserman, P., Monte Carlo Methods in Financial Engineering. New York: Springer-Verlag, 2004.
Hull, J., Options, Futures, and Other Derivatives, 5th. edition. Upper Saddle River, New Jersey: Prentice Hall, 2003.
Merton, R.C., On the pricing when underlying stock returns are discontinuous, Journal of Financial Economics, (3) 1976, pp. 125-144.
Download Help Document