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    A reality check on the GARCH-MIDAS volatility models

    Virk, Nadar ORCID logoORCID: https://orcid.org/0000-0001-6338-2198, Javed, Farrukh, Awartani, Basel and Hyde, Stuart (2024) A reality check on the GARCH-MIDAS volatility models. The European Journal of Finance, 30 (6). pp. 575-596. ISSN 1351-847X

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    Abstract

    We employ a battery of model evaluation tests for a broad set of GARCH-MIDAS models and account for data snooping bias. We document that inferences based on standard tests for GM variance components can be misleading. Our data mining free results show that the gain of macro-variables in forecasting total (long-run) variance by GM models is overstated (understated). Estimation of different components of volatility is crucial for designing differentiated investing strategies, risk management plans and pricing derivative securities. Therefore, researchers and practitioners should be wary of data-mining bias, which may contaminate a forecast that may appear statistically validated using robust evaluation tests.

    Item Type: Article (Article)
    Peer-reviewed: Yes
    Date Deposited: 27 Nov 2023 14:02
    Publisher: Taylor & Francis
    Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in The European Journal of Finance on 8th June 2023, available at: https://doi.org/10.1080/1351847X.2023.2217220. It is deposited under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Divisions: Faculties > Business and Law
    Subject terms: 1502 Banking, Finance and Investment, Finance
    URI: https://mmu-uat.leaf.cosector.com/id/eprint/633396
    DOI: https://doi.org/10.1080/1351847X.2023.2217220
    ISSN 1351-847X
    e-ISSN 1466-4364

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