International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

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:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

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ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8


FEATURE PEER-REVIEWED ARTICLE

Vol.13(10)(2022)

  • Do Islamic Stock Indices Follow the Adaptive Market Hypothesis Using an Artificial Neural Network Approach?

    Muhammad Shariq (Nust Business School, National University of Sciences &Technology, Islamabad, PAKISTAN),
    Muhammad Ashfaq (Department of Finance and Accounting, IU International University of Applied Sciences, GERMANY),
    Usman Ayub (Department of Management Sciences, COMSATS University Islamabad, PAKISTAN),
    Attayah Shafique (Department of Management Sciences, COMSATS University Islamabad, PAKISTAN and Department of Communication and Management Sciences, Pakistan Institute of Engineering and Applied Sciences, Islamabad, PAKISTAN),
    Sidra Israr Bukhari (Department of Management Sciences, COMSATS University Islamabad, PAKISTAN).

    Discipline: Management Sciences (Finance), Data Science & Deep Learning.

    ➤ FullText

    doi: 10.14456/ITJEMAST.2022.194

    Keywords: Efficient market hypothesis (EMH); Behavioral finance; Varying efficiency; Inefficiency of market index; Islamic market; Adaptive market hypothesis (AMH).

    Abstract
    The purpose of this study is to determine the existence of the adaptive market hypothesis (AMH) in Islamic stock indices as a growing substitute to efficient market hypothesis (EMH) by employing monthly returns of Karachi Meezan Index 30 and S&P 500 Shariah are used which cover three main regions of capital investments. To fulfill the purpose, monthly returns from 2010 to 2019 are inspected. Artificial Neural Network Approach and Rolling Window Analysis are applied in this study. Hence, the outcomes show markets' efficiency after some time, which bolsters the AMH in Islamic markets. The essential outcome is that the Islamic stock exchanges accomplished noteworthy cyclical patterns of predictable and non-predictable returns over the period which bolsters the AMH idea. The research outcomes would provide help to brokers and portfolio managers as well as investors to encapsulate valuable returns over Islamic markets.

    Paper ID: 13A10E

    Cite this article:

    Shariq, M., Ashfaq, M., Ayub, U., Shafique. A., and Bukhari, S.I. (2022). Do Islamic Stock Indices Follow the Adaptive Market Hypothesis Using an Artificial Neural Network Approach?. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 13(10), 13A10E, 1-9. http://TUENGR.COM/V13/13A10E.pdf DOI: 10.14456/ITJEMAST.2022.194

References

  1. Abdelsalam, O. and El-Komi, M. (2014). Islamic finance: an introduction. Journal of economic behavior and organization., 103(Supplement), S1-S3.
  2. Al-Khazali, O.M., Leduc, G. and Alsayed, M.S. (2016). A market efficiency comparison of Islamic and non-Islamic stock indices. Emerging Markets Finance and Trade, 52(7), 1587-1605.
  3. Campbell, J.Y., Lo, A. and MacKinlay, C. (1997). The econometrics of financial markets. Princeton University Press, Princeton. New Jersey: MacKinlay.
  4. Charles, A., Darne, O. and Kim, J.H. (2017). Adaptive markets hypothesis for Islamic stock indices: Evidence from Dow Jones size and sector-indices. International Economics, 151, 100-112.
  5. El Khamlichi, A., Sarkar, K., Arouri, M. and Teulon, F. (2014). Are Islamic equity indices more efficient than their conventional counterparts? Evidence from major global index families. Journal of Applied Business Research, 30(4), 1137-1150.
  6. Hussein, K. and Omran, M. (2005). Ethical investment revisited: evidence from Dow Jones Islamic indexes. The Journal of Investing, 14(3), 105-126.
  7. Hiremath, G. S., and Kumari, J. (2013). Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India. SpringerPlus, 3(1), 1-14.
  8. Ho, C.S.F., Abd Rahman, N.A., Yusuf, N.H.M. and Zamzamin, Z. (2014). Performance of global Islamic versus conventional share indices: International evidence. Pacific-Basin Finance Journal, 28, 110-121.
  9. Hull, M. and McGroarty, F. (2014). Do emerging markets become more efficient as they develop? Long memory persistence in equity indices. Emerging Markets Review, 18, 45-61.
  10. Jawadi, F. and Jawadi, N., Idi Cheffou A (2014). Are Islamic Stock Markets Efficient: A Time-Series Analysis. Appl Econ, 47(16), 1686-1697.
  11. Kim, J.H., Shamsuddin, A. and Lim, K.P. (2011). Stock return predictability and the adaptive markets hypothesis: Evidence from century-long US data. Journal of Empirical Finance, 18(5), 868-879.
  12. Lim, K.P. and Hooy, C.W. (2013). Non-Linear Predictability in G7 Stock Index Returns. The Manchester School, 81(4), 620-637.
  13. Lo, A.W. (2004). The adaptive markets hypothesis. The Journal of Portfolio Management, 30(5), 15-29.
  14. Manahov, V. and Hudson, R. (2014). A note on the relationship between market efficiency and adaptability-New evidence from artificial stock markets. Expert Systems with Applications, 41(16), 7436-7454.
  15. Mohammad, N. and Ashraf, D. (2015). The market timing ability and return performance of Islamic equities: An empirical study. Pacific-Basin Finance Journal, 34, 169-183.
  16. Rizvi, S.A.R., Dewandaru, G., Bacha, O.I. and Masih, M. (2014). An analysis of stock market efficiency: Developed vs Islamic stock markets using MF-DFA. Physica A: Statistical Mechanics and its Applications, 407, 86-99.
  17. Rana, M.E. and Akhter, W. (2015). Performance of Islamic and conventional stock indices: empirical evidence from an emerging economy. Financial Innovations, 1(1), 1-17.
  18. Sewell, M. (2014). Efficient Markets Hypothesis: Joint Hypothesis.
  19. Shahid, M.N. and Sattar, A. (2017). Behavior of calendar anomalies, market conditions and adaptive market hypothesis: evidence from Pakistan stock exchange. Pakistan Journal of Commerce and Social Science, 11(2), 471-504.
  20. Urquhart, A. and Hudson, R. (2013). Efficient or adaptive markets? Evidence from major stock markets using very long run historic data. International Review of Financial Analysis, 28, 130-142.
  21. Urquhart, A. and McGroarty, F. (2014). Calendar effects, market conditions and the Adaptive Market Hypothesis: Evidence from long-run US data. International Review of Financial Analysis, 35, 154-166.


Other issues:
Vol.13(9)(2022)
Vol.13(8)(2022)
Vol.13(7)(2022)
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