Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities

Francisco Jareño and Imran Yousaf

International Review of Financial Analysis, 2023, vol. 89, issue C

Abstract: The main focus of this research is to investigate the potential spillover effects between AI-based stocks and tokens by using the quantile connectedness approach developed by Ando et al. (2022). The study aims to investigate both static and dynamic spillovers at the lower and upper tails of the return distribution. AI-based stocks and tokens may have relatively low levels of connectedness, which also varies over time and increases during periods of economic turbulence. In addition, in line with previous work analysing other financial markets and assets, this research finds that the system is more sensitive to the tails of the distribution (i.e., the lower and upper quantiles) than to the median (Q = 0.50). This finding is consistent with expectations, and measures of dynamic connectedness change over time, with the intensity of spillovers increasing at the extremes of the distribution. These results have practical implications for portfolio managers, as they can use the results to adjust their investment portfolios according to the evolution of the dynamic spillovers observed in the system. Overall, this study sheds light on the potential tail spillovers in the AI-based stock and token market and provides valuable insights for investment decisions.

Keywords: Artificial intelligence-based tokens; Artificial intelligence-based stocks; Quantile connectedness; COVID-19 pandemic crisis period; Russia-Ukraine war period (search for similar items in EconPapers)
JEL-codes: C22 C51 L61 Q02 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:89:y:2023:i:c:s1057521923003423

DOI: 10.1016/j.irfa.2023.102826

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