The Effect of the Coronavirus Pandemic on the Prediction Accuracy of Stock Price

Jia-Yen Huang and Wei-Zhen Lin
Additional contact information
Jia-Yen Huang: Department of Information Management, National Chin-Yi University of Technology, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung City 41170, Taiwan, R.O.C.
Wei-Zhen Lin: Department of Information Management, National Chin-Yi University of Technology, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung City 41170, Taiwan, R.O.C.

International Journal of Information Technology & Decision Making (IJITDM), 2023, vol. 22, issue 01, 569-588

Abstract: In late 2019, the coronavirus began to spread around the world and impact international politics and economies significantly. In the face of the pandemic, stock markets around the world fluctuated sharply. The study aims to investigate the impact of the pandemic on the predictive variables of a stock prediction model, formed using chip-based variables and sentiment variables derived from comments posted on a social media platform. This study first performs feature engineering analysis to identify the indicators suitable for constructing the prediction model. The analysis then establishes a set of phrase rules to assign sentiment scores to the opinions expressed in replies and evaluates the effect on the accuracy of predictions. The results show that the major chip-based indicators affecting changes in the stock market differ before and after the pandemic. Hence, prediction models should be established separately for analysis in either period. In addition, the results indicate that the model relying on reply-based sentiment scores as a predictive variable provides more accurate predictions of stock price change.

Keywords: COVID-19 pandemic; prediction accuracy; logistic regression; social media replies; phrase rules; sentiment scores (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622022500468
Access to full text is restricted to subscribers

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:wsi:ijitdm:v:22:y:2023:i:01:n:s0219622022500468

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622022500468

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().