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In what way can worldwide robotics and artificial intelligence encourage development in green crypto investments? An implementation of a model-free connectedness technique

Le Thanh Ha (Faculty of Economics, National Economics University, Hanoi, Vietnam)

Studies in Economics and Finance

ISSN: 1086-7376

Article publication date: 31 May 2024

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Abstract

Purpose

This study aims to investigate connections between the development of robotic and artificial intelligence (AI) and green crypto investments. The author also explores the influences of global uncertainty shocks like the COVID-19 pandemic and international conflicts on the role of each channel.

Design/methodology/approach

In this research, the author uses a cutting-edge model-free connectedness approach to investigate the relationships between the development of Global X Robotics and AI (BOTZ) and the volatility of green crypto investments from November 9, 2017 to March 24, 2023.

Findings

In the sample duration, the findings reveal a two-way link between AI and green/nongreen cryptocurrencies. Throughout the examined period, BOTZ has been a net receiver of shocks as determined by the net total connectedness. Among the main spillover shock carriers in the system, green cryptocurrencies are the most significant. The net pairwise directional connectivity reveals that green cryptocurrencies controlled BOTZ throughout the analyzed time, particularly during the COVID-19 era as well as the Ukraine–Russia crisis. According to the findings, the proposed system is vulnerable to a high level of indication influence.

Practical implications

The results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

Originality/value

To the best of the authors’ knowledge, this paper is the first to look at the link between AI, technological advancement and green cryptocurrency investing. Second, this study developed a methodology for examining instability links between various factors that is more appropriate for investigating these linkages. This study investigates the links between AI, technical advancement and green digital currencies using a cutting-edge model-free connectivity method. This work is also the first to examine the interconnection between volatility derived from AI, technological development and green cryptocurrency investments in light of unknown events, such as the COVID-19 pandemic and the Ukrainian–Russian conflict. Finally, this study includes a daily database from the BOTZ fund, which attempts to invest in firms that stand to gain from rising robotics and AI use. Cardano (ADA), IOTA, NANO (XNO), Stellar Lumens and Tron are examples of green cryptocurrencies, whereas Bitcoin is an example of a nongreen cryptocurrency. These virtual currencies are being used to investigate the relationship between investor mood and green and nongreen digital currencies. The data set spans the period from November 9, 2017 to March 24, 2023.

Keywords

Acknowledgements

This paper was sopported by National Economics University.

Declaration of interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethics approval and consent to participate: Not applicable.

Consent for publication: Not applicable.

Compliance with ethical standards:

• Disclosure of potential conflicts of interest.

• Research involving human participants and/or animals.

• Informed consent.

Data availability statement: Data available on request due to privacy/ethical restrictions.

Citation

Ha, L.T. (2024), "In what way can worldwide robotics and artificial intelligence encourage development in green crypto investments? An implementation of a model-free connectedness technique", Studies in Economics and Finance, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/SEF-11-2023-0668

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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