Tail connectedness between artificial intelligence tokens, artificial intelligence ETFs, and traditional asset classes

IF 5.4 2区经济学 Q1 BUSINESS, FINANCE Journal of International Financial Markets Institutions & Money Pub Date : 2023-12-30 DOI:10.1016/j.intfin.2023.101929

Imran Yousaf , Manel Youssef , John W. Goodell

{"title":"Tail connectedness between artificial intelligence tokens, artificial intelligence ETFs, and traditional asset classes","authors":"Imran Yousaf , Manel Youssef , John W. Goodell","doi":"10.1016/j.intfin.2023.101929","DOIUrl":null,"url":null,"abstract":"<div><p>We examine extreme connectedness between the artificial intelligence (AI) tokens, artificial intelligence ETFs, and other asset classes, using the quantile VAR approach of <span>Ando et al., (2022)</span><span><span>. We find moderate connectedness levels at mean and median quantiles, with AI ETFs (AI tokens) acting as strong (weak) net emitters (receivers) of return spillovers. Findings, confirmed by alternative testing, suggest that, during normal market conditions, AI tokens may offer utility as diversifiers for portfolios of traditional assets. However, at both lower and upper quantiles, connectedness levels increase, consistent with AI tokens and ETFs being sensitive to extreme shocks. Results suggest that AI tokens and ETFs do not diversify the risk of other assets during extreme market conditions. Finally, AI tokens, especially, may offer effective hedging at low cost for traditional assets (gold, equity, real estate, bonds, and currency), except for the oil and </span>cryptocurrency market. Investors including AI assets in portfolios need to diligently monitor for changing market conditions.</span></p></div>","PeriodicalId":48119,"journal":{"name":"Journal of International Financial Markets Institutions & Money","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2023-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of International Financial Markets Institutions & Money","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S104244312300197X","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}

引用次数: 0

Abstract

We examine extreme connectedness between the artificial intelligence (AI) tokens, artificial intelligence ETFs, and other asset classes, using the quantile VAR approach of Ando et al., (2022). We find moderate connectedness levels at mean and median quantiles, with AI ETFs (AI tokens) acting as strong (weak) net emitters (receivers) of return spillovers. Findings, confirmed by alternative testing, suggest that, during normal market conditions, AI tokens may offer utility as diversifiers for portfolios of traditional assets. However, at both lower and upper quantiles, connectedness levels increase, consistent with AI tokens and ETFs being sensitive to extreme shocks. Results suggest that AI tokens and ETFs do not diversify the risk of other assets during extreme market conditions. Finally, AI tokens, especially, may offer effective hedging at low cost for traditional assets (gold, equity, real estate, bonds, and currency), except for the oil and cryptocurrency market. Investors including AI assets in portfolios need to diligently monitor for changing market conditions.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

人工智能代币、人工智能 ETF 和传统资产类别之间的尾部关联性

我们使用 Ando 等人（2022 年）的量化 VAR 方法研究了人工智能代币、人工智能 ETF 和其他资产类别之间的极端关联性。我们发现，在平均值和中位数量级上，人工智能 ETF（人工智能代币）的关联度适中，是回报溢出效应的强（弱）净发射器（接收器）。经替代测试确认的研究结果表明，在正常市场条件下，人工智能代币可作为传统资产投资组合的多样化工具。然而，在较低和较高的量级上，关联度水平都会增加，这与人工智能代币和 ETF 对极端冲击的敏感性是一致的。结果表明，在极端市场条件下，人工智能代币和 ETF 无法分散其他资产的风险。最后，除石油和加密货币市场外，人工智能代币尤其可以为传统资产（黄金、股票、房地产、债券和货币）提供低成本的有效对冲。将人工智能资产纳入投资组合的投资者需要密切关注不断变化的市场环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of International Financial Markets Institutions & Money Multiple-

CiteScore

6.60

自引率

10.00%

发文量

142

期刊介绍： International trade, financing and investments, and the related cash and credit transactions, have grown at an extremely rapid pace in recent years. The international monetary system has continued to evolve to accommodate the need for foreign-currency denominated transactions and in the process has provided opportunities for its ongoing observation and study. The purpose of the Journal of International Financial Markets, Institutions & Money is to publish rigorous, original articles dealing with the international aspects of financial markets, institutions and money. Theoretical/conceptual and empirical papers providing meaningful insights into the subject areas will be considered. The following topic areas, although not exhaustive, are representative of the coverage in this Journal. • International financial markets • International securities markets • Foreign exchange markets • Eurocurrency markets • International syndications • Term structures of Eurocurrency rates • Determination of exchange rates • Information, speculation and parity • Forward rates and swaps • International payment mechanisms • International commercial banking; • International investment banking • Central bank intervention • International monetary systems • Balance of payments.