Bounded Influence Estimation for Auto-Regressive Conditional Heteroskedasticity Models with Estimates of the Variances of Foreign Exchange Rates

This paper proposes a robust estimation procedure, the bounded influence estimate (BIE), that is robust against departure from the conditional normality of the autoregressive conditional heteroskedasticity (ARCH) models to describe the behavior of exchange rates. First, the BIE identifies the additive outliers (AO, e.g., Fox 1972) caused by abnormal information arrivals which may be triggered by changes in domestic policies and international shocks. Identification of outliers allows us to analyze the major economic and political factors that contribute directly to the dramatic changes in exchange rates. Second, the performance of the BIE is compared with the maximum likelihood estimate (MLE) and a semiparametric estimator (SP) of Engle and Gonzalez-Rivera (1991)