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

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  • Jareño, Francisco
  • Yousaf, Imran

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.

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  • Jareño, Francisco & Yousaf, Imran, 2023. "Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities," International Review of Financial Analysis, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:finana:v:89:y:2023:i:c:s1057521923003423
    DOI: 10.1016/j.irfa.2023.102826
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    More about this item

    Keywords

    Artificial intelligence-based tokens; Artificial intelligence-based stocks; Quantile connectedness; COVID-19 pandemic crisis period; Russia-Ukraine war period;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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