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Unveiling Outperformance: A Portfolio Analysis of Top AI-Related Stocks against IT Indices and Robotics ETFs

Author

Listed:
  • Ali Trabelsi Karoui

    (Laboratory BESTMOD, University of Sfax, Sfax 3029, Tunisia)

  • Sonia Sayari

    (College of Business Admiration and Finance, Saudi Electronic University, Riyadh 11673, Saudi Arabia)

  • Wael Dammak

    (Institute of Financial and Insurance Sciences, University of Lyon, University Claude Bernard Lyon 1, LSAF-EA2429, F-69007 Lyon, France)

  • Ahmed Jeribi

    (Faculty of Economics and Management of Mahdia, University of Monastir, Monastir 5000, Tunisia)

Abstract

In this study, we delve into the financial market to compare the performance of prominent AI and robotics-related stocks against traditional IT indices, such as the Nasdaq, and specialized AI and robotics ETFs. We evaluate the role of these stocks in diversifying portfolios, analyzing their return potential and risk profiles. Our analysis includes various investment scenarios, focusing on common AI-related stocks in the United States. We explore the influence of risk management strategies, ranging from “buy and hold” to daily rebalancing, on AI stock portfolios. This involves investigating long-term strategies like buy and hold, as well as short-term approaches, such as daily rebalancing. Our findings, covering the period from 30 April 2021, to 15 September 2023, show that AI-related stocks have not only outperformed in recent years but also highlight the growing “AI bubble” and the increasing significance of AI in investment decisions. The study reveals that these stocks have delivered superior performance, as indicated by metrics like Sharpe and Treynor ratios, providing insights into market trends and financial returns in the technology and robotics sectors. The results are particularly relevant for investors and traders in the AI sector, offering a balanced view of potential returns against the risks in this rapidly evolving market. This paper adds to the financial market literature by demonstrating that investing in emerging trends, such as AI, can be more advantageous in the short term compared to traditional markets like the Nasdaq.

Suggested Citation

  • Ali Trabelsi Karoui & Sonia Sayari & Wael Dammak & Ahmed Jeribi, 2024. "Unveiling Outperformance: A Portfolio Analysis of Top AI-Related Stocks against IT Indices and Robotics ETFs," Risks, MDPI, vol. 12(3), pages 1-21, March.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:3:p:52-:d:1356521
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    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    2. An-Sing Chen & James Wuh Lin, 2014. "The relation between gold and stocks: an analysis of severe bear markets," Applied Economics Letters, Taylor & Francis Journals, vol. 21(3), pages 158-170, February.
    3. Emmanuel Joel Aikins Abakah & Aviral Kumar Tiwari & Chi‐Chuan Lee & Matthew Ntow‐Gyamfi, 2023. "Quantile price convergence and spillover effects among Bitcoin, Fintech, and artificial intelligence stocks," International Review of Finance, International Review of Finance Ltd., vol. 23(1), pages 187-205, March.
    4. Yu, Jing-Rung & Lee, Wen-Yi, 2011. "Portfolio rebalancing model using multiple criteria," European Journal of Operational Research, Elsevier, vol. 209(2), pages 166-175, March.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    6. Fredj Jawadi & Nabila Jawadi & Duc Khuong Nguyen & Hassan Obeid, 2013. "Information technology sector and equity markets: an empirical investigation," Applied Financial Economics, Taylor & Francis Journals, vol. 23(9), pages 729-737, May.
    7. Smales, L.A., 2019. "Bitcoin as a safe haven: Is it even worth considering?," Finance Research Letters, Elsevier, vol. 30(C), pages 385-393.
    8. Dammak, Wael & Hamad, Salah Ben & de Peretti, Christian & Eleuch, Hichem, 2023. "Pricing of European currency options considering the dynamic information costs," Global Finance Journal, Elsevier, vol. 58(C).
    9. Ortas, Eduardo & Moneva, José M., 2013. "The Clean Techs equity indexes at stake: Risk and return dynamics analysis," Energy, Elsevier, vol. 57(C), pages 259-269.
    10. Philip Fei Wu & Jessica Vitak & Michael T. Zimmer, 2020. "A contextual approach to information privacy research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(4), pages 485-490, April.
    11. Wael Dammak & Salah Ben Hamad & Christian de Peretti & Hichem Eleuch, 2023. "Pricing of European currency options considering the dynamic information costs," Post-Print hal-04875463, HAL.
    12. Aurore J. Kamssu & Brian J. Reithel & Jennifer L. Ziegelmayer, 2003. "Information Technology and Financial Performance: The Impact of being an Internet-Dependent Firm on Stock Returns," Information Systems Frontiers, Springer, vol. 5(3), pages 279-288, September.
    13. Dowling, Michael & Lucey, Brian, 2023. "ChatGPT for (Finance) research: The Bananarama Conjecture," Finance Research Letters, Elsevier, vol. 53(C).
    14. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
    15. Scott Willenbrock, 2011. "Diversification Return, Portfolio Rebalancing, and the Commodity Return Puzzle," Papers 1109.1256, arXiv.org.
    16. Scott Willenbrock, 2011. "Diversification Return, Portfolio Rebalancing, and the Commodity Return Puzzle," Financial Analysts Journal, Taylor & Francis Journals, vol. 67(4), pages 42-49, July.
    17. Ramona Rupeika-Apoga & Stefan Wendt, 2022. "FinTech Development and Regulatory Scrutiny: A Contradiction? The Case of Latvia," Risks, MDPI, vol. 10(9), pages 1-13, August.
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    1. Dammak, Wael & Frikha, Wajdi & Souissi, Mohamed Naceur, 2024. "Market turbulence and investor decision-making in currency option market," The Journal of Economic Asymmetries, Elsevier, vol. 30(C).

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