Connectedness of AI and Islamic stocks: Evidence from frequency-domain quantile regressions
John Gartchie Gatsi, Samuel Kwaku Agyei, Peterson Owusu, Gorkel Obro-Adibo
- Year
- 2025
- Citations
- 2
- Access
- Open access
Abstract
This study explores the dynamic relationship between artificial intelligence (AI)-based stocks and Islamic stock indices. Motivated by the rising prominence of AI in global finance and the ethical appeal of Islamic investing, the study investigates whether AI stocks offer hedging, diversification, or safe haven potential relative to Islamic assets. Daily data from January 1, 2019, to April 13, 2024, is employed, covering the NASDAQ CTA Artificial Intelligence and Robotics Index (as the proxy for AI stocks), along with the Dow Jones Islamic Market World Index, United States and Canada. Using the Empirical Mode Decomposition (EEMD) with Quantile Regression techniques, the analysis captures the asymmetric relationships across different investment horizons and market states. The results reveal that AI stocks generally move in tandem with Islamic stock indices during stable and bullish markets, offering limited diversification benefits. However, in bearish markets, particularly over the long term, AI stocks exhibit a negative relationship with the global and U.S. Islamic indices, indicating potential safe haven or hedging roles. No such hedging benefit is observed concerning the Canadian Islamic index. Additionally, Islamic indices do not serve as effective hedges for AI stocks across any market regime. These results offer detailed insights into the asymmetric co-movement patterns between AI-related stocks and Islamic equities. It offers practical implications for ethical and tech-focused investors, suggesting that AI stocks may enhance portfolio resilience under specific market conditions. Policymakers and financial product designers can also leverage these insights to integrate emerging technologies into Shariah-compliant investment strategies better.
Keywords
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