| int __stdcall NDK_GARCH_SIM | ( | double | mu, |
| 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] 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 of the latest observations (a one dimensional array). [in] nSize is the number of observations in pData. [in] sigmas is the univariate time series of the latest observations (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
-
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g. #N/A) at either end.
- The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
- The number of parameters in the input argument - beta - determines the order of the GARCH component model.
- By definition, the GARCH_FORE function returns a constant value equal to the model mean (i.e. \(\mu\)) for all horizons.
- The function GARCH_SIM was added in version 1.63 SHAMROCK.
- Requirements
-
Header SFSDK.H Library SFSDK.LIB DLL SFSDK.DLL
| Namespace: | NumXLAPI |
| Class: | SFSDK |
| Scope: | Public |
| Lifetime: | Static |
| int NDK_GARCH_SIM | ( | double | mu, |
| 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] 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 of the latest observations (a one dimensional array). [in] nSize is the number of observations in pData. [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
-
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g. #N/A) at either end.
- The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
- The number of parameters in the input argument - beta - determines the order of the GARCH component model.
- By definition, the GARCH_FORE function returns a constant value equal to the model mean (i.e. \(\mu\)) for all horizons.
- The function GARCH_SIM was added in version 1.63 SHAMROCK.
- Exceptions
-
Exception Type Condition None N/A
- Requirements
-
Namespace NumXLAPI Class SFSDK Scope Public Lifetime Static Package 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
