TY - JOUR
T1 - Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets
T2 - Another look using quantile-based approaches
AU - Abakah, Emmanuel Joel Aikins
AU - Tiwari, Aviral Kumar
AU - Ghosh, Sudeshna
AU - Doğan, Buhari
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/7
Y1 - 2023/7
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Bitcoin
KW - Causality in quantiles
KW - Cross-quantilogram correlation
KW - Fintech
KW - Predictability
UR - http://www.scopus.com/inward/record.url?scp=85152485944&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2023.122566
DO - 10.1016/j.techfore.2023.122566
M3 - Article
AN - SCOPUS:85152485944
SN - 0040-1625
VL - 192
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 122566
ER -