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

Shahid Raza, Sun Baiqing (), Pwint Kay-Khine and Muhammad Ali Kemal
Additional contact information
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

IJFS, 2023, vol. 11, issue 3, 1-25

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.

Keywords: stock market; KSE-100 index; OLS; ARCH; GARCH; Pakistan Stock Exchange (search for similar items in EconPapers)
JEL-codes: F2 F3 F41 F42 G1 G2 G3 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2227-7072/11/3/99/pdf (application/pdf)
https://www.mdpi.com/2227-7072/11/3/99/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijfss:v:11:y:2023:i:3:p:99-:d:1210725

Access Statistics for this article

IJFS is currently edited by Ms. Hannah Lu

More articles in IJFS from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().