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http://bura.brunel.ac.uk/handle/2438/27390Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Caporale, GM | - |
| dc.contributor.author | de Dios Mazariegos, JJ | - |
| dc.contributor.author | Gil-Alana, LA | - |
| dc.date.accessioned | 2023-10-16T14:13:12Z | - |
| dc.date.available | 2023-10-16T14:13:12Z | - |
| dc.date.issued | 2024-03-13 | - |
| dc.identifier | ORCID iD: Guglielmo Maria Caporale https://orcid.org/0000-0002-0144-4135 | - |
| dc.identifier | ORCiD: Luis A. Gil-Alana https://orcid.org/0000-0002-5760-3123 | - |
| dc.identifier.citation | Caporale, G.M., de Dios Mazariegos, J.J. and Gil-Alana, L.A. (2024) 'Long-run linkages between US stock prices and cryptocurrencies: a fractional cointegration analysis', Computational Economics, 0 (ahead of print), pp. 1 - 11. doi: 10.1007/s10614-023-10510-3. | en_US |
| dc.identifier.issn | 0927-7099 | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27390 | - |
| dc.description | JEL Classification: C22; C58; G11; G15. | - |
| dc.description.abstract | This paper applies fractional integration and cointegration methods to examine respectively the univariate properties of the four main cryptocurrencies in terms of market capitalization (BTC, ETH, USDT, BNB) and of four US stock market indices (S&P500, NASDAQ, Dow Jones and MSCI for emerging markets) as well as the possible existence of long-run linkages between them. Daily data from 9 November 2017 to 28 June 2022 are used for the analysis. The results provide evidence of market efficiency in the case of the cryptocurrencies but not of the stock market indices considered. The results also indicate that in most cases there are no long-run equilibrium relationships linking the assets in question, which implies that cryptocurrencies can be a useful tool for investors to diversify and hedge when required in the case of the US markets. | - |
| dc.description.sponsorship | Grant PID2020-113691RB-I00 funded by MCIN/AEI/10. 13039/ 501100011033. | en_US |
| dc.format.extent | 1 - 11 | - |
| dc.format.medium | Print-Electronic | - |
| dc.language.iso | en_US | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.rights | Copyright © 2024 The Author(s). Rights and permissions: Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/. | - |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
| dc.subject | stock market prices | en_US |
| dc.subject | cryptocurrencies | en_US |
| dc.subject | persistence | en_US |
| dc.subject | fractional integration and cointegration | en_US |
| dc.title | Long-run linkages between US stock prices and cryptocurrencies: a fractional cointegration analysis | en_US |
| dc.type | Article | en_US |
| dc.identifier.doi | https://doi.org/10.1007/s10614-023-10510-3 | - |
| dc.relation.isPartOf | Computational Economics | - |
| pubs.publication-status | Published online | - |
| pubs.volume | 0 | - |
| dc.identifier.eissn | 1572-9974 | - |
| dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
| dc.rights.holder | The Author(s) | - |
| Appears in Collections: | Dept of Economics and Finance Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2024 The Author(s). Rights and permissions: Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/. | 947.29 kB | Adobe PDF | View/Open |
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