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Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis

Author

Listed:
  • Shahid Raza

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Sun Baiqing

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Pwint Kay-Khine

    (School of Management, Harbin Institute of Technology, Harbin 150001, China)

  • Muhammad Ali Kemal

    (SDGs Unit, Ministry of Planning, Development and Special Initiatives, Islamabad 44030, Pakistan)

Abstract

The stock markets in developing countries are highly responsive to breaking news and events. Our research explores the impact of economic conditions, financial policies, and politics on the KSE-100 index through daily market news signals. Utilizing simple OLS regression and ARCH/GARCH regression methods, we determine the best model for analysis. The results reveal that political and global news has a significant impact on KSE-100 index. Blue chip stocks are considered safer investments, while short-term panic responses often overshadow rational decision-making in the stock market. Investors tend to quickly react to negative news, making them risk-averse. Our findings suggest that the ARCH/GARCH models are better at predicting stock market fluctuations compared to the simple OLS method.

Suggested Citation

  • Shahid Raza & Sun Baiqing & Pwint Kay-Khine & Muhammad Ali Kemal, 2023. "Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis," IJFS, MDPI, vol. 11(3), pages 1-25, August.
    • Handle: RePEc:gam:jijfss:v:11:y:2023:i:3:p:99-:d:1210725
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    References listed on IDEAS

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    Cited by:

    1. Santosh KUMAR & Bharat Kumar MEHER & Ramona BIRAU & Abhishek ANAND & Mircea Laurentiu SIMION, 2023. "Investigating Volatility Dynamics of the Portugal Stock Market using FIGARCH Models," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 39-45.

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