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Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches

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  • Abakah, Emmanuel Joel Aikins
  • Tiwari, Aviral Kumar
  • Ghosh, Sudeshna
  • Doğan, Buhari

Abstract

Against the milieu of rapidly growing investment in technologically induced assets, this study examines the investment role of Bitcoin, fintech, and artificial intelligence (AI) stocks in relation to major environmentally friendly assets (green bonds, sustainable investments, and clean energy), Islamic stocks, and conventional financial markets using quantile-based approaches. To this end, we specifically examine the distributional and directional predictability between the returns of fintech, Bitcoin, and AI and various markets using the nonparametric causality-in-quantiles method and the cross-quantilogram correlation method respectively. We use daily data spanning March 9, 2018 to January 27, 2021. In terms of the distributional predictability of fintech, Bitcoin, and AI in relation to the traditional markets, Islamic stocks, clean energy stocks, and sustainable investments, we find strong evidence of causal asymmetry across quantiles and strong variations across markets. Likewise, findings in terms of directional predictability between the returns of fintech, Bitcoin, and AI and various markets infer that Islamic stocks act as a good hedge against Bitcoin. The S&P Treasury Bond and S&P Green Bond are also perfect hedges for fintech stocks, while S&P Global Clean Energy is a perfect hedge for AI stocks in terms of long-term dynamics.

Suggested Citation

  • Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Ghosh, Sudeshna & Doğan, Buhari, 2023. "Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:tefoso:v:192:y:2023:i:c:s0040162523002512
    DOI: 10.1016/j.techfore.2023.122566
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    Cited by:

    1. Song, Lina & Li, Wenting & Yang, Yandi & Gao, Hongyu & Du, Xinqiang & Jia, Xinlin, 2024. "Understanding the impact of Fintech, and Mineral Resources on Artificial Intelligence currency: A global evidence from QARDL Approach," Resources Policy, Elsevier, vol. 95(C).
    2. Peng, Yue & Wang, Wei & Zhen, Shangsong & Liu, Yunqiang, 2024. "Does digitalization help green consumption? Empirical test based on the perspective of supply and demand of green products," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    3. Liu, Lei & Rasool, Zeeshan & Ali, Sajid & Wang, Canghong & Nazar, Raima, 2024. "Robots for sustainability: Evaluating ecological footprints in leading AI-driven industrial nations," Technology in Society, Elsevier, vol. 76(C).
    4. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2024. "Tail connectedness between artificial intelligence tokens, artificial intelligence ETFs, and traditional asset classes," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    5. Xie, Wenhao & Cao, Guangxi, 2024. "Volatility and returns connectedness between cryptocurrency and China’s financial markets: A TVP-VAR extended joint connectedness approach," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    6. Lei, Heng & Xue, Minggao & Ye, Jing, 2024. "The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications," Energy Economics, Elsevier, vol. 132(C).
    7. Dong, Xueqin & Huang, Lilong, 2024. "Exploring ripple effect of oil price, fintech, and financial stress on clean energy stocks: A global perspective," Resources Policy, Elsevier, vol. 89(C).
    8. Ben Jabeur, Sami & Gozgor, Giray & Rezgui, Hichem & Mohammed, Kamel Si, 2024. "Dynamic dependence between quantum computing stocks and Bitcoin: Portfolio strategies for a new era of asset classes," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    9. Zeng, Hongjun & Abedin, Mohammad Zoynul & Zhou, Xiangjing & Lu, Ran, 2024. "Measuring the extreme linkages and time-frequency co-movements among artificial intelligence and clean energy indices," International Review of Financial Analysis, Elsevier, vol. 92(C).
    10. Sun, Yizhong & Jin, Keyan & Wang, Deyong & Wu, Qingyang & Li, Zhezhou, 2023. "Revisiting the natural resources-financial development nexus in China: The importance of economic policy uncertainty," Resources Policy, Elsevier, vol. 86(PB).
    11. Afshan, Sahar & Leong, Ken Yien & Najmi, Arsalan & Razi, Ummara & Lelchumanan, Bawani & Cheong, Calvin Wing Hoh, 2024. "Fintech advancements for financial resilience: Analysing exchange rates and digital currencies during oil and financial risk," Resources Policy, Elsevier, vol. 88(C).
    12. Yousaf, Imran & Ijaz, Muhammad Shahzad & Umar, Muhammad & Li, Yanshuang, 2024. "Exploring volatility interconnections between AI tokens, AI stocks, and fossil fuel markets: evidence from time and frequency-based connectedness analysis," Energy Economics, Elsevier, vol. 133(C).
    13. Wu, Jiawen & Li, Jing-Ping & Su, Chi-Wei, 2024. "Can green bond hedges climate policy uncertainty in the United States: New insights from novel time-varying causality and quantile-on-quantile methods?," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 1158-1176.
    14. Zhang, Xincheng, 2024. "Country-level energy-related uncertainties and stock market returns: Insights from the U.S. and China," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    15. Zhu, Yi & Lin, Yangyi & Tan, Yanyu & Liu, Bin & Wang, Hao, 2024. "The potential nexus between fintech and energy consumption: A new perspective on natural resource consumption," Resources Policy, Elsevier, vol. 89(C).

    More about this item

    Keywords

    Fintech; Bitcoin; Artificial intelligence; Predictability; Causality in quantiles; Cross-quantilogram correlation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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