Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics
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DOI: 10.1080/14697688.2020.1751257
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Cited by:
- Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
- Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
- Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
- Naimoli, Antonio, 2023. "The information content of sentiment indices in forecasting Value at Risk and Expected Shortfall: a Complete Realized Exponential GARCH-X approach," International Economics, Elsevier, vol. 176(C).
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