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Download a pdf copy of this help file here |
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Download a pdf copy of this help file here |
See also: Time series in ModelRisk
VoseTimeGBMMR(Mu,Sigma,Alpha,R0,LogReturn,{TimeStamps},LastValue)
Array
function that models a Geometric
Brownian Motion (GBM) with Mean Reversion time series model, meaning
the variable is drawn back towards its long-run mean in proportion to
its deviation from the mean.
GBM is usually the default starting point for a time series of a non-negative financial variable - like a stock price, exchange rate or interest rate. It assumes that the fractional changes in the variable between periods are independent, random variables following a Normal distribution.
Mu - the percentage drift.
Sigma - the percentage volatility.
Alpha - the mean reversion factor.
R0 - logreturn at period 0.
LastValue - last known historic value. The generated time series values will continue on from this value. Should only be provided if the LogReturn parameter is set to FALSE or omitted.
{TimeStamps} - array of time stamps. Needs to be the same size as the output array
LogReturn - Optional boolean parameter (TRUE/FALSE) specifying whether to return the actual time series (FALSE, default) or log returns (TRUE).
As the ModelRisk Time Series functions typically take a lot of parameters, we recommend for these in particular to use the Time Series window.
VoseTimeGBMMR - generates an array of random values from this time series.
VoseTimeGBMMRFit - generates an array of random values from this time series fitted to data.
VoseTimeGBMMRFitP - returns the parameters of this time series fitted to data.