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Computing the Time-Varying Effects of Investor Attention in Islamic Stock Returns

Author

Listed:
  • Nabila Jawadi

    (IPAG Business School)

  • Fredj Jawadi

    (University of Lille)

  • Abdoulkarim Idi Cheffou

    (ISG Paris Business School)

Abstract

This paper investigates the relationship between investor attention and the Islamic stock market. In particular, we investigate whether investor attention—measured by Google searches—could help to improve the forecasting of Islamic stock returns. To this end, we used quantile regressions to examine the relationship over the period 2004–2016 in order to capture its evolution during calm and turbulent times. We thus investigated the effect of investor attention not only on the mean, but also for the different quantiles. Our findings highlight two important points. First, the relationship between investor attention and Islamic stock returns exhibits time-variation and nonlinearity as investor attention significantly impacts the dynamics of Islamic returns, but its sign and effect vary per quantile. Second, the usefulness of information provided by investor attention improves the forecasting of future Islamic stock returns.

Suggested Citation

  • Nabila Jawadi & Fredj Jawadi & Abdoulkarim Idi Cheffou, 2020. "Computing the Time-Varying Effects of Investor Attention in Islamic Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 131-143, June.
    • Handle: RePEc:kap:compec:v:56:y:2020:i:1:d:10.1007_s10614-020-09988-y
    DOI: 10.1007/s10614-020-09988-y
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    Cited by:

    1. Andini Nurul Aini & Citra Sukmadilaga & Erlane K. Ghani, 2023. "Green Bonds, Investor Attention and Stock Market Reaction: Evidence from ASEAN Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 334-343, November.
    2. Yamini Yadav & Pramod Kumar Naik, 2024. "Investors’ Irrational Sentiment and Stock Market Returns: A Quantile Regression Approach Using Indian Data," Business Perspectives and Research, , vol. 12(1), pages 45-64, January.
    3. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    4. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Saleem, Owais & Adeoye, Habeeb A., 2022. "Asymmetric connectedness between Google-based investor attention and the fourth industrial revolution assets: The case of FinTech and Robotics & Artificial intelligence stocks," Technology in Society, Elsevier, vol. 68(C).

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    More about this item

    Keywords

    Investor attention; Islamic stock market; Quantile regression; Out-of-sample forecasting;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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