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Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices

Hongjun Zeng, Mohammad Abedin, Xiangjing Zhou, Ran Lu

International Review of Financial Analysis, Volume: 92, Start page: 103073

Swansea University Author: Mohammad Abedin

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DOI (Published version): 10.1016/j.irfa.2024.103073

Published in: International Review of Financial Analysis
ISSN: 1057-5219
Published: Elsevier BV 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65445
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first_indexed 2024-01-11T21:26:35Z
last_indexed 2024-01-11T21:26:35Z
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spelling v2 65445 2024-01-11 Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices 4ed8c020eae0c9bec4f5d9495d86d415 Mohammad Abedin Mohammad Abedin true false 2024-01-11 BAF Journal Article International Review of Financial Analysis 92 103073 Elsevier BV 1057-5219 Artificial intelligence; Clean energy; Tail risk; Quantile time-frequency; Wavelet; Quantile granger causality 1 3 2024 2024-03-01 10.1016/j.irfa.2024.103073 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2024-03-21T11:17:04.0655334 2024-01-11T21:24:34.2131083 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Hongjun Zeng 1 Mohammad Abedin 2 Xiangjing Zhou 3 Ran Lu 4 65445__29776__f786a5ba2929469ca4ce91556ea1a943.pdf 65445_AAM.pdf 2024-03-21T11:15:22.8432810 Output 443249 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/2.0/deed.en
title Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
spellingShingle Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
Mohammad Abedin
title_short Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
title_full Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
title_fullStr Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
title_full_unstemmed Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
title_sort Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Mohammad Abedin
author Mohammad Abedin
author2 Hongjun Zeng
Mohammad Abedin
Xiangjing Zhou
Ran Lu
format Journal article
container_title International Review of Financial Analysis
container_volume 92
container_start_page 103073
publishDate 2024
institution Swansea University
issn 1057-5219
doi_str_mv 10.1016/j.irfa.2024.103073
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance
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published_date 2024-03-01T11:17:01Z
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