Applied Econometrics

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Box-Jenkins methodology ● Recall: purpose of ARIMA models – univariate decomposition of time series, goal: extract all statistically significant components ● Box-Jenkins methodology: ● Identification: stationarity and order of integration, identify p and q. ● Estimation: use software package and do not care about the details (usually non-linear least squares or maximum likelihood method). ● Model Validation: ACF and PACF insignificant, minimized information criteria.
ARIMA models in JMulti ● Data: PX/PX-50 index and CEZ stock 2001-06 ● In a lecture: does the PX50 time series follows the random walk? The result is that it is not. ● Stationarity? Order of integration to achieve stationarity? Use the ADF test. ● ACF and PACF of transformed series. What number of p and q? ● Estimation and analysis of residuals. ● Note: automatic model selection with the Hannan-Rissanen procedure: h...ĺogT
Page 1 and 2: Applied Econometrics Seminar: ARIMA
Page 3: ARMA and ARIMA Models ● Just the
Page 8 and 9: Comments to the results ● Still s
Page 10 and 11: GARCH and ARCH - Summary ● ARCH -
Page 12 and 13: ● But: Squares of log returns - v
Page 14 and 15: ● Plots for residuals of CEZ ARIM

Applied Econometrics

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