observations. Conversely, neglected outliers in a linear time series of moderate length may incorrectly suggest STAR type … have a better level and power behavior than standard nonrobust tests in situations with outliers. We formally derive local … time series sometimes seems due to only a small number of outliers. …

In this paper the issue of detecting and handling outliers in the GARCH(1,1) model is addressed. Simulation evidence … shows that neglecting even a single outlier has a dramatic on parameter estimates. To detect and correct for outliers, we … shows that correcting for a few outliers yields substantial improvements in out-of-sample forecasts. …

, periods with outliers) which differ in length and size. In this paper we put forward a new model which can describe and …

LM test that is resistant to additive outliers. The data span two samples of 5 years ranging from 1986 to 1995. Our main … empirical method, we show that this general finding indeed appears to be due to outliers. We discuss some of the implications of …

heteroskedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AO's). We show analytically that both the … due to only a small number of outliers and, conversely, that genuine GARCH effects can be masked by outliers. …

Outliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to examine and compare the …