Hizmeri, Rodrigo, Izzeldin, Marwan, Nolte, Ingmar and Pappas, Vasileios
(2022)
A generalized heterogeneous autoregressive model using market information.
QUANTITATIVE FINANCE, 22 (8).
pp. 1513-1534.
ISSN 1469-7688, 1469-7696
Abstract
This paper introduces a novel class of volatility forecasting models that incorporate market realized (co)variances and semi(co)variances within the framework of a heterogeneous autoregressive (HAR) model. Our empirical analysis shows statistically and economically significant forecasting gains. For our most parsimonious market-HAR specification, stock volatility forecasting is improved by 9.80% points. Using a mixed sampling frequency market-HAR variant with low (high) sampling frequency for the stock (market) improves forecasting by a further 6.90% points. Our paper also develops noise-robust estimators to facilitate the use of realized semi(co)variances at high sampling frequencies.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Realized volatility, Microstructure noise, Pre-averaged estimators, Semi-variance, Semi-covariance, Volatility forecasting |
| Divisions: | Faculty of Humanities and Social Sciences > School of Management |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 08 Jun 2022 14:21 |
| Last Modified: | 07 Dec 2024 23:24 |
| DOI: | 10.1080/14697688.2022.2076606 |
| Open Access URL: | https://doi.org/10.1080/14697688.2022.2076606 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3155472 |
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