# NDK_GARCHM_SIM

 int __stdcall NDK_GARCHM_SIM ( double mu, double flambda, const double * Alphas, size_t p, const double * Betas, size_t q, WORD nInnovationType, double nu, double * pData, size_t nSize, double * sigmas, size_t nSigmaSize, UINT nSeed, double * retArray, size_t nSteps )

Returns a simulated data series the underlying GARCH process.

Returns
status code of the operation
Return values
 NDK_SUCCESS Operation successful NDK_FAILED Operation unsuccessful. See Macros for full list.
Parameters
 [in] mu is the GARCH model conditional mean (i.e. mu). [in] flambda is the volatility coefficient for the mean. In finance, lambda is referenced as the risk premium. [in] Alphas are the parameters of the ARCH(p) component model (starting with the lowest lag). [in] p is the number of elements in Alphas array [in] Betas are the parameters of the GARCH(q) component model (starting with the lowest lag). [in] q is the number of elements in Betas array [in] nInnovationType is the probability distribution function of the innovations/residuals (see INNOVATION_TYPE) [in] nu is the shape factor (or degrees of freedom) of the innovations/residuals probability distribution function. [in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of observations in pData. [in] sigmas is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last q realized volatilities. [in] nSigmaSize is the number of elements in sigmas. Only the latest q observations are used. [in] nSeed is an unsigned integer for setting up the random number generators [out] retArray is the calculated simulation value [in] nSteps is the number of future steps to simulate for.
Remarks
1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The time series may include missing values (e.g. #N/A) at either end.
4. The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
5. The number of parameters in the input argument - beta - determines the order of the GARCH component model.
6. The function GARCHM_SIM was added in version 1.63 SHAMROCK.
Requirements
 Namespace: NumXLAPI Class: SFSDK Scope: Public Lifetime: Static
 int NDK_GARCHM_SIM ( double mu, double flambda, double[] Alphas, UIntPtr p, double[] Betas, UIntPtr q, short nInnovationType, double nu, double[] pData, UIntPtr nSize, UIntPtr nSeed, ref double retVal, UIntPtr nSteps )

Returns a simulated data series the underlying GARCH process.

Return Value

a value from NDK_RETCODE enumeration for the status of the call.

 NDK_SUCCESS operation successful Error Error Code
Parameters
 [in] mu is the GARCH model conditional mean (i.e. mu). [in] flambda is the volatility coefficient for the mean. In finance, lambda is referenced as the risk premium. [in] Alphas are the parameters of the ARCH(p) component model (starting with the lowest lag). [in] p is the number of elements in Alphas array [in] Betas are the parameters of the GARCH(q) component model (starting with the lowest lag). [in] q is the number of elements in Betas array [in] nInnovationType is the probability distribution function of the innovations/residuals (see INNOVATION_TYPE) [in] nu is the shape factor (or degrees of freedom) of the innovations/residuals probability distribution function. [in] pData is the univariate time series data (a one dimensional array). [in] nSize is the number of observations in X. [in] sigmas is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last q realized volatilities. [in] nSigmaSize is the number of elements in sigmas. Only the latest q observations are used. [in] nSeed is an unsigned integer for setting up the random number generators [out] retArray is the calculated simulation value [in] nSteps is the number of future steps to simulate for.
Remarks
1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The time series may include missing values (e.g. #N/A) at either end.
4. The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
5. The number of parameters in the input argument - beta - determines the order of the GARCH component model.
6. The function GARCHM_SIM was added in version 1.63 SHAMROCK.
Exceptions
Exception Type Condition
None N/A
Requirements
Namespace NumXLAPI SFSDK Public Static NumXLAPI.DLL
Examples

References
* Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
* Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740
* D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906
* Box, Jenkins and Reisel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848