IGARCH effect on autoregressive lag length selection and causality tests
Using Monte Carlo experiments, we show how information criteria determine, in the presence of GARCH errors, an optimal lag length in univariate time series and causality tests. We illustrate the simulations by testing the presence of serial correlation in exchange rates as well as Granger-causality between interest rates.
Volume (Year): 3 (1996)
Issue (Month): 5 ()
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