MS Banking and Finance

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INTERDEPENDENCY BETWEEN CRYPTOCURRENCIES, ARTIFICIAL INTELLIGENCE & FINTECH STOCKS
(UMT.Lahore, 2023-12-28) AMOON AKHTAR
This study investigates the interlinkages and interdependencies among non-traditional tech based asset classes, including cryptocurrency, FinTech, and AI & Robotics indices, employing wavelet coherence analysis in a time-frequency horizon. It offers a fresh perspective on the potential benefits of hedging, diversification, and acting as a safe haven within the tech-based market under study. The research utilizes daily data from ten global indices spanning from March 1st, 2017, to March 3rd, 2023. The results suggest that the co-movements within the tech based market are time-frequency dependent. Overall, the findings indicate a weak association among tech-based markets, suggesting they remain decoupled during periods of market uncertainty and turbulence. However, the study also reveals instances of heightened correlation during turbulent events, indicating herding behavior among investors. These findings have significant implications for investors and portfolio managers in terms of safe haven, hedging and diversification benefits as well as for the authorities, policy makers and regulators regarding policy development which mitigate financial risk