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The last decade has seen substantial advances in the measurement, modeling and forecasting of volatility which has centered around the realized volatility literature. To date, most of the focus has been on the daily and monthly frequency, with little attention on longer horizons such as the...
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In this paper, we show the effects that outliers have on estimation and inference for autoregressive conditional heteroskedasticity (ARCH) models. We propose for a wide class of ARCH models commonly estimated, an empirically tractable solution to this problem by replacing outliers with their...
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