Description Usage Arguments Value Author(s) References Examples
See Maior and Cysneiros (2018) for details on this function.
1 |
model |
a result of a call to |
h |
number of periods for forecasting. If xreg is used, h is ignored and the number of forecast periods is set to the number of rows of xreg. |
xreg |
future values of an regression variables. |
pred |
predicted values. |
Vinicius Quintas Souto Maior and Francisco Jose A. Cysneiros
Maintainer: Vinicius Quintas Souto Maior <vinicius@de.ufpe.br>
Brockwell, P. J. and Davis, R. A. (1991). Time Series and Forecasting Methods. Second edition. Springer, New York. Section 11.4.
Brockwell, P. J. and Davis, R. A. (1996). Introduction to Time Series and Forecasting. Springer, New York. Sections 5.1 and 7.6.
Maior, V. Q. S. and Cysneiros, F. J. A. (2018). SYMARMA: a new dynamic model for temporal data on conditional symmetric distribution. Statitical Paper, 59, 75-97. doi: 10.1007/s00362-016-0753-z.
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attach(assets)
# Return in the prices on Microsoft and SP500 index
N = length(msf)
.sp500 = ((sp500[2:N]-sp500[1:(N-1)])/sp500[1:(N-1)])*100
.msf = ((msf[2:N]-msf[1:(N-1)])/msf[1:(N-1)])*100
# The T-bill rates were divided by 253 to convert to a daily rate
.tbill = tbill/253
# Excess return in the d prices on Microsoft and SP500 index
Y = .msf - .tbill[1:(N-1)]
X = .sp500 - .tbill[1:(N-1)]
# Period from April 4, 2002 to October 4, 2002
serie = Y[2122:2240]
aux = cbind(X[2122:2240])
# Fit SYMARMA models
fit.1 = elliptical.ts(serie,order=c(0,0,1),include.mean=FALSE,
family="Normal")
# Forecasts
predict(fit.1, h=10)
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