Finance[Diffusion] - compute the diffusion component of an Ito process
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Calling Sequence
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Diffusion(X)
Diffusion(f, mu, sigma, X, t)
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Parameters
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X
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stochastic process, expression involving stochastic variables
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f
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algebraic expression involving stochastic variables
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mu
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algebraic expression, drift term of the original process
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sigma
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algebraic expression, diffusion term of the original process
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X
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name, stochastic variable
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t
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name, time variable
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Description
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The Diffusion(X) calling sequence computes the diffusion term of an Ito process X. That is, given a process governed by the stochastic differential equation (SDE)
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the Diffusion command will return .
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The parameter X can be either a stochastic process or an expression involving stochastic variables. In the first case a Maple procedure is applied for computing the diffusion term. This procedure will accept two parameters: the value of the state variable and the time, and return the corresponding value of the diffusion. In the second case, Ito's lemma will be applied to calculate the diffusion term of X. Note that the Diffusion command will perform formal computations; the validity of these computations for a given function f will not be verified.
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Compatibility
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The Finance[Diffusion] command was introduced in Maple 15.
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Examples
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The Diffusion command determines how to compute the diffusion and volatility for all supported Ito-type processes.
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You can also use expressions involving stochastic variables.
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The following example deals with two correlated one-dimensional Wiener processes.
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See Also
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Finance[BrownianMotion], Finance[CEVProcess], Finance[DeterministicProcess], Finance[Drift], Finance[GaussMarkovProcess], Finance[GeometricBrownianMotion], Finance[HestonProcess], Finance[OrnsteinUhlenbeckProcess], Finance[SquareRootDiffusion], Finance[StochasticProcesses], Finance[WienerProcess]
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References
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Glasserman, P., Monte Carlo Methods in Financial Engineering. New York: Springer-Verlag, 2004.
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Hull, J., Options, Futures, and Other Derivatives, 5th. edition. Upper Saddle River, New Jersey: Prentice Hall, 2003.
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Kloeden, P., and Platen, E., Numerical Solution of Stochastic Differential Equations, New York: Springer-Verlag, 1999.
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