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Finance[ItoProcess] - create new Ito process
Calling Sequence
ItoProcess(, mu, sigma)
ItoProcess(, mu, sigma, x, t)
ItoProcess(X, Sigma)
Parameters
-
the initial value
mu
the drift parameter
sigma
volatility parameter
X
Vector of one-dimensional Ito processes
Sigma
matrix
Description
The ItoProcess command creates a new one- or multi-dimensional Ito process, which is a stochastic process governed by the stochastic differential equation (SDE)
where
is the drift parameter
is the diffusion parameter
and
is the standard Wiener process.
The parameter defines the initial value of the underlying stochastic process. It must be a real constant.
The parameter mu is the drift. In the simplest case of a constant drift mu is real number (that is, any expression of type realcons). Time-dependent drift can be given either as an algebraic expression or as a Maple procedure. If mu is given as an algebraic expression, then the parameter t must be passed to specify which variable in mu should be used as a time variable. A Maple procedure defining a time-dependent drift must accept one parameter (the time) and return the corresponding value for the drift.
The parameter sigma is the diffusion. Similar to the drift parameter, the volatility can be constant or time-dependent.
One can use the ItoProcess command to construct a multi-dimensional Ito process with the given correlation structure. To be more precise, assume that is an -dimensional vector whose components , ..., are one-dimensional Ito processes. Let ,...,, and ,..., be the corresponding drift and diffusion terms. The ItoProcess(X, Sigma) command will create an -dimensional Ito process such that
where is an -dimensional Wiener process whose covariance matrix is Sigma. Note that the matrix Sigma must have numeric coefficients.
Compatibility
The Finance[ItoProcess] command was introduced in Maple 15.
For more information on Maple 15 changes, see Updates in Maple 15.
Examples
You can generate sample paths for this stochastic process (in order to do this, we must assign numeric values to mu and sigma).
Here is an example of a multi-dimensional Ito process.
In this example, construct a two-dimensional Ito process using two one-dimensional projections and a given covariance matrix.
See Also
Finance[BlackScholesProcess], Finance[CEVProcess], Finance[Diffusion], Finance[Drift], Finance[ExpectedValue], Finance[GeometricBrownianMotion], Finance[ItoProcess], Finance[PathPlot], Finance[SamplePath], Finance[SampleValues], Finance[StochasticProcesses], Finance[WienerProcess]
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.
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