Short Patches of Outliers, ARCH and Volatility Modeling
نویسندگان
چکیده
In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G)ARCH] in daily data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a LM test that is resistant to patches of additive outliers. The data span two samples of 5 years ranging from 1986 to 1995. Using asymptotic arguments and Monte Carlo simulations, in which we evaluate our empirical method, we show that patches of outliers can have signi cant e ects on test outcomes. Our main empirical result is that we nd spurious GARCH in about 40% of the cases, while in many other cases we nd evidence of GARCH even though such sequences of extraordinary observations seem to be present.
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