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Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion

Miklesh Prasad Yadav, Mohammad Abedin, Neena Sinha, Vandana Arya

Research in International Business and Finance, Volume: 67, Start page: 102146

Swansea University Author: Mohammad Abedin

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Abstract

This paper investigates the connectedness of Artificial intelligence stocks with agri-commodity stocks during COVID-19 and Russia-Ukraine invasion. To measure the Artificial intelligence stocks, we consider Microsoft, Google, Amazon, Meta and NVIDA while US wheat, US corn, US soyabean, US oats and U...

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Published in: Research in International Business and Finance
ISSN: 0275-5319 1878-3384
Published: Elsevier BV 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64915
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last_indexed 2023-11-03T23:48:07Z
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spelling v2 64915 2023-11-03 Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion 4ed8c020eae0c9bec4f5d9495d86d415 Mohammad Abedin Mohammad Abedin true false 2023-11-03 BAF This paper investigates the connectedness of Artificial intelligence stocks with agri-commodity stocks during COVID-19 and Russia-Ukraine invasion. To measure the Artificial intelligence stocks, we consider Microsoft, Google, Amazon, Meta and NVIDA while US wheat, US corn, US soyabean, US oats and US Rice are proxied to represent the agri-commodity stocks. The daily closing price of these stocks is taken from December 31, 2019 to February 23, 2022 (COVID-19) and February 24, 2022 to August 10, 2022 (Russia-Ukraine Invasion). For an empirical estimation, Diebold & Yilmaz (2012) and Barunik & Krehlik (2018) models are employed to investigate the connectedness among these assets class. The result reveals that Microsoft is highest receiver as well as highest contributor of the shocks; US rice and US corn are least receiver and contributor of the shocks respectively during COVID-19 period. Journal Article Research in International Business and Finance 67 102146 Elsevier BV 0275-5319 1878-3384 Artificial intelligence, Agri-commodity, Connectedness, COVID-19, Russia-Ukraine Invasion 31 1 2024 2024-01-31 10.1016/j.ribaf.2023.102146 http://dx.doi.org/10.1016/j.ribaf.2023.102146 COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2023-12-04T14:39:46.4847072 2023-11-03T23:47:31.7236759 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Miklesh Prasad Yadav 1 Mohammad Abedin 2 Neena Sinha 3 Vandana Arya 4 64915__29198__cb2a402a9f1c4c0e8874a87f2498ed72.pdf 64915.VOR.pdf 2023-12-04T14:35:40.0665631 Output 3671170 application/pdf Version of Record true © 2023 The Authors. Published by Elsevier B.V. Distributed under the terms of a Creative Commons Attribution 4.0 International License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/
title Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
spellingShingle Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
Mohammad Abedin
title_short Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
title_full Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
title_fullStr Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
title_full_unstemmed Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
title_sort Uncovering dynamic connectedness of Artificial intelligence stocks with agri-commodity market in wake of COVID-19 and Russia-Ukraine Invasion
author_id_str_mv 4ed8c020eae0c9bec4f5d9495d86d415
author_id_fullname_str_mv 4ed8c020eae0c9bec4f5d9495d86d415_***_Mohammad Abedin
author Mohammad Abedin
author2 Miklesh Prasad Yadav
Mohammad Abedin
Neena Sinha
Vandana Arya
format Journal article
container_title Research in International Business and Finance
container_volume 67
container_start_page 102146
publishDate 2024
institution Swansea University
issn 0275-5319
1878-3384
doi_str_mv 10.1016/j.ribaf.2023.102146
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
url http://dx.doi.org/10.1016/j.ribaf.2023.102146
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description This paper investigates the connectedness of Artificial intelligence stocks with agri-commodity stocks during COVID-19 and Russia-Ukraine invasion. To measure the Artificial intelligence stocks, we consider Microsoft, Google, Amazon, Meta and NVIDA while US wheat, US corn, US soyabean, US oats and US Rice are proxied to represent the agri-commodity stocks. The daily closing price of these stocks is taken from December 31, 2019 to February 23, 2022 (COVID-19) and February 24, 2022 to August 10, 2022 (Russia-Ukraine Invasion). For an empirical estimation, Diebold & Yilmaz (2012) and Barunik & Krehlik (2018) models are employed to investigate the connectedness among these assets class. The result reveals that Microsoft is highest receiver as well as highest contributor of the shocks; US rice and US corn are least receiver and contributor of the shocks respectively during COVID-19 period.
published_date 2024-01-31T14:39:47Z
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