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Investor overreaction and global financial crisis: A case of Pakistan stock exchange

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  • Bahrawar Said
  • Shafiq Ur Rehman
  • Rizwan Ullah
  • Javed Khan
  • David McMillan

Abstract

Recently, the investor overreaction catches the attention of the academicians and practitioners. The topic comes under the limelight of academicians and policymakers. This study, therefore, addresses investor overreaction and its relationship with the global financial crisis for the period of 2004–15. The study used stratified random sampling technique; equal allocation method of Krejcie and Morgan. By adopting the methodology of Debondt and Thaler, the study finds that there is highly significant overreaction (distinct reversal) in the stock market in the global-financial crisis period, which may attribute to the aggressive behavior of individual investors in the market. Overreaction has also been shown in the line graph shaded area which opposes the efficient market hypothesis and verifies the presence of a weak form of efficiency. Econometric tests are applied for robustness check that confirms weak form of efficiency in the PSX. The study has implications for both the investors and policymakers. This study is quintessential for those investors who have the aptitude to look introspectively and to evaluate their behavioral biases. Further, investors would learn to transmute behaviors and to build portfolios which will help them to stick to their long-term investment strategies and hence achieve their investment goals.

Suggested Citation

  • Bahrawar Said & Shafiq Ur Rehman & Rizwan Ullah & Javed Khan & David McMillan, 2021. "Investor overreaction and global financial crisis: A case of Pakistan stock exchange," Cogent Economics & Finance, Taylor & Francis Journals, vol. 9(1), pages 1966195-196, January.
  • Handle: RePEc:taf:oaefxx:v:9:y:2021:i:1:p:1966195
    DOI: 10.1080/23322039.2021.1966195
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    Cited by:

    1. Asif Ali & Habib Ur Rahman & Adam Arian & John Sands, 2023. "Flight-to-Liquidity and Excess Stock Return: Empirical Evidence from a Dynamic Panel Model," JRFM, MDPI, vol. 16(12), pages 1-16, December.
    2. Abdul Karim & Abdul Rasheed, 2024. "Forecasting Modeling of Day of the Week Calendar Anomalies in Pakistan Stock Exchange: An Artificial Intelligence Perspective," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(2), pages 436-447.

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