Natural Disaster Risk and Firm Performance: Text Mining and Machine Learning Approach

70 Pages Posted: 5 Sep 2023

See all articles by Minh Nguyen

Minh Nguyen

Michigan State University

Ting-Tsen Ye

Louisiana State University, Shreveport

Yuanzhang Xiao

University of Hawaii at Manoa

Shirley Daniel

University of Hawaii at Manoa - School of Accountancy

Date Written: August 26, 2023

Abstract

We develop a perceived measure of firms’ disaster exposure and/or preparedness equal to the number of words related to natural disaster events in the firms’ Form 10-Ks. We then link this measure to contemporary and future firm decision-making and performance. We find that this perceived natural disaster risk and the government-reported damages of natural hazards this year are negatively associated with firm profitability next year. However, the perceived natural disaster risk is not associated with sales growth and Tobin's Q ratio. Specifically, the perceived natural disaster risk negatively affects firm profitability in the services sector but not in the manufacturing sector. The firm profitability in the services sector is also negatively affected by the billion-dollar natural disasters in the same year. Finally, we find that advanced machine learning models robustly outperform linear regression in predicting firm performance under natural disaster risks. The main implication from this study is that we can employ textual data in financial reports to measure the perceived natural disaster risk and predict its effects on firm performance.

Keywords: Natural disaster risk, firm performance, Form 10-Ks, text mining, machine learning

JEL Classification: C45, C53, L25, M21, Q51, Q54

Suggested Citation

Nguyen, Minh and Ye, Ting-Tsen and Xiao, Yuanzhang and Daniel, Shirley, Natural Disaster Risk and Firm Performance: Text Mining and Machine Learning Approach (August 26, 2023). Available at SSRN: https://ssrn.com/abstract=4552483 or http://dx.doi.org/10.2139/ssrn.4552483

Minh Nguyen (Contact Author)

Michigan State University ( email )

632 Business College Complex, Rm N218
East Lansing, MI 48824
United States

HOME PAGE: http://https://sites.google.com/view/minhn/

Ting-Tsen Ye

Louisiana State University, Shreveport

Yuanzhang Xiao

University of Hawaii at Manoa

Shirley Daniel

University of Hawaii at Manoa - School of Accountancy ( email )

College of Business Administration
Honolulu, HI 96822
United States

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