Autoregressive Lag Length Selection Criteria in the Presence of ARCH Errors
We study the effects of ARCH errors on the performance of the commonly used lag length selection criteria. The most important finding of this study is that SIC, FPE, HQC and BIC perform considerably well in estimating the true autoregressive lag length, even in the presence of ARCH errors. Thus, we conclude that these criteria are applicable to empirical data such as stock market returns and exchange rate volatility that exhibit ARCH effects.
Volume (Year): 3 (2005)
Issue (Month): 19 ()
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NBER Working Papers
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