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V = forecast(model,numPeriods)
V = forecast(model,numPeriods,Name,Value)
V = forecast(model,numPeriods) forecasts the conditional variance of a GJR process over a specified forecast horizon.
V = forecast(model,numPeriods,Name,Value) generates forecasts with additional options specified by one or more Name,Value pair arguments.
model 
gjr model object, as created by gjr or estimate. The input model object cannot have any NaN values. 
numPeriods 
Positive integer specifying the forecast horizon, in periods consistent with the underlying GJR model and the sampling frequency of any presample data. 
Specify optional commaseparated pairs of Name,Value arguments. Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.
Notes

[1] Baillie, R., and T. Bollerslev. "Prediction in Dynamic Models with TimeDependent Conditional Variances." Journal of Econometrics. Vol. 52, 1992, pp. 91–113.
[2] Bollerslev, T. "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics. Vol. 31, 1986, pp. 307–327.
[3] Bollerslev, T. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return." The Review of Economics and Statistics. Vol. 69, 1987, pp. 542–547.
[4] Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. Time Series Analysis: Forecasting and Control. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994.
[5] Enders, W. Applied Econometric Time Series. Hoboken, NJ: John Wiley & Sons, 1995.
[6] Engle, R. F. "Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation." Econometrica. Vol. 50, 1982, pp. 987–1007.
[7] Glosten, L. R., R. Jagannathan, and D. E. Runkle. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks." The Journal of Finance. Vol. 48, No. 5, 1993, pp. 1779–1801.
[8] Hamilton, J. D. Time Series Analysis. Princeton, NJ: Princeton University Press, 1994.
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