(deprecated) Calculates the estimated error/standard deviation of the conditional mean forecast.
Syntax
GARCHM_FORESD(X, Sigmas, Order, mean, lambda, alphas, betas, T, Local)
- X
- is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last p observations.
- Sigmas
- is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last q realized volatilities.
- Order
- is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)).
Order Description 1 ascending (the first data point corresponds to the earliest date) (default) 0 descending (the first data point corresponds to the latest date) - mean
- is the GARCH-M model mean (i.e. mu).
- lambda
- is the volatility coefficient for the mean. In finance, lambda is referenced as the risk premium.
- alphas
- are the parameters of the ARCH(p) component model (starting with the lowest lag).
- betas
- are the parameters of the GARCH(q) component model (starting with the lowest lag).
- T
- is the forecast time horizon (expressed in terms of steps beyond the end of the time series X). If missing, t=1 is assumed.
- Local
- is the type of desired volatility output (0=Term Structure, 1=Local Volatility). If missing, local volatility is assumed.
Warning
GARCHM_FORESD() function is deprecated as of version 1.63: use GARCHM_FORE function instead.
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.
Examples
Example 1:
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Formula | Description (Result) |
---|---|
=GARCHM_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,1) | Forecasted conditional volatility at T+1, February 10, 2008 (0.9966) |
=GARCHM_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,2) | Forecasted conditional volatility at T+2, February 11, 2008 (0.9966) |
=GARCHM_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,3) | Forecasted conditional volatility at T+3, February 12, 2008 (0.9966) |
Files 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
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