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DC Field | Value | Language |
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dc.contributor.author | Yfanti, S | - |
dc.contributor.author | Karanasos, M | - |
dc.date.accessioned | 2022-03-09T19:47:50Z | - |
dc.date.available | 2022-03-09T19:47:50Z | - |
dc.date.issued | 2021-08-23 | - |
dc.identifier | ORCID iD: Stavroula Yfanti https://orcid.org/0000-0001-8071-916X | - |
dc.identifier | ORCID iD: Menelaos Karanasos https://orcid.org/0000-0001-5442-3509 | - |
dc.identifier.citation | Yfanti, S. and Karanasos, M. (2021) 'Financial volatility modeling with option-implied information and important macro-factors', Journal of the Operational Research Society, 73 (9), pp. 2129 - 2149. doi: 10.1080/01605682.2021.1966327. | en_US |
dc.identifier.issn | 0160-5682 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/24221 | - |
dc.description.abstract | Copyright © 2021 The Author(s). The research debate on the informational content embedded in option prices mostly approves the incremental predictive power of implied volatility estimates for financial volatility forecasting beyond that contained in GARCH and realized variance models. Contributing to this ongoing debate, we introduce the novel AIM-HEAVY model, a tetravariate system with asymmetries, option-implied volatility, and economic uncertainty variables beyond daily and intra-daily dispersion measures included in the benchmark HEAVY specification. We associate financial with macroeconomic uncertainties to explore the macro-financial linkages in the high-frequency domain. In this vein, we further focus on economic factors that exacerbate stock market volatility and represent major threats to financial stability. Hence, our findings are directly connected to the current world-wide Coronavirus outbreak. Financial volatilities are already close to their crisis-peaks amid the generalized fear about controversial economic policies to support societies and the financial system, especially in the case of the heavily criticized UK authorities’ delayed and limited response. | en_US |
dc.format.extent | 2129 - 2149 | - |
dc.format.medium | Print-Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Routledge (Taylor & Francis Group) | en_US |
dc.rights | Copyright © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (https://creativecommons.org/ licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | - |
dc.rights.uri | https://creativecommons.org/ licenses/by-nc-nd/4.0/ | - |
dc.subject | economic policy uncertainty | en_US |
dc.subject | high-frequency data | en_US |
dc.subject | implied volatility | en_US |
dc.subject | macro-financial linkages | en_US |
dc.subject | realized variance | en_US |
dc.subject | risk management | en_US |
dc.title | Financial volatility modeling with option-implied information and important macro-factors | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1080/01605682.2021.1966327 | - |
dc.relation.isPartOf | Journal of the Operational Research Society | - |
pubs.issue | 9 | - |
pubs.publication-status | Published | - |
pubs.volume | 73 | - |
dc.identifier.eissn | 1476-9360 | - |
dc.rights.holder | The Author(s) | - |
Appears in Collections: | Dept of Economics and Finance Research Papers |
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File | Description | Size | Format | |
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FullText.pdf | Copyright © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (https://creativecommons.org/ licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. | 3.02 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License