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Realized volatility forecasting: Robustness to measurement errors
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DOI：10.1016/j.ijforecast.2020.02.009.png)
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In this paper, we suggest how to handle the issue of the heteroskedasticity of measurement errors when specifying dynamic models for the conditional expectation of realized variance. We show that either adding a GARCH correction within an asymmetric extension of the HAR class (AHAR-GARCH), or working within the class of asymmetric multiplicative error models (AMEM) greatly reduces the need for quarticity/quadratic terms to capture attenuation bias. This feature in AMEM can be strengthened by considering regime specific dynamics. Model Confidence Sets confirm this robustness both in- and out-of-sample for a panel of 28 big caps and the S&P500 index. (C) 2020 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keyword:
Realized volatility
Forecasting
Measurement errors
HAR
AMEM
Markov switching
Volatility of volatility
MCS
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