Bladt, Martin and McNeil, Alexander John orcid.org/0000-0002-6137-2890 (2022) Time series copula models using d-vines and v-transforms. Econometrics and Statistics. 27-48. ISSN 2452-3062
Abstract
An approach to modelling volatile financial return series using stationary d-vine copula processes combined with Lebesgue-measure-preserving transformations known as v-transforms is proposed. By developing a method of stochastically inverting v-transforms, models are constructed that can describe both stochastic volatility in the magnitude of price movements and serial correlation in their directions. In combination with parametric marginal distributions it is shown that these models can rival and sometimes outperform well-known models in the extended GARCH family.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s). |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > The York Management School |
Depositing User: | Pure (York) |
Date Deposited: | 01 Mar 2023 12:40 |
Last Modified: | 16 Oct 2024 17:44 |
Published Version: | https://doi.org/10.1016/j.ecosta.2021.07.004 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.ecosta.2021.07.004 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:196923 |
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Description: Time series copula models using d-vines and v-transforms
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