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The Impact of Natural Disasters on Stock Prices in China: A Comparative Analysis of State-Owned and Privately Owned Enterprises

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The Impact of Natural Disasters on Stock Prices in China: A Comparative Analysis of State-Owned and Privately Owned Enterprises

Liu, Shurui ORCID: https://orcid.org/0009-0002-8933-8843 (2024) The Impact of Natural Disasters on Stock Prices in China: A Comparative Analysis of State-Owned and Privately Owned Enterprises. Masters thesis, Concordia University.

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Abstract

This paper examines the impact of natural disasters on corporate stock price performance in China, with a particular focus on state-owned enterprises (SOEs) and privately owned enterprises (POEs). Utilizing an event study methodology, we analyze the stock price reactions of Chinese companies to large-scale tropical cyclones from 2000 to 2022. Our findings indicate that these natural disasters have a significant negative impact on stock prices, particularly during the immediate impact period. SOEs, however, demonstrate greater resilience compared to POEs during the post-disaster recovery period, suggesting that political connections and government support provide advantages in mitigating market volatility. Cross-sectional regression analyses reveal that firms with high leverage, low profitability, smaller size, and low market valuation experience higher abnormal returns in the recovery phase, indicating a faster recovery rate. An industry-specific analysis further shows that the financial services sector performs better following natural disasters, potentially due to increased demand for financial products, access to government aid, and favorable investor sentiment.

Divisions:Concordia University > John Molson School of Business > Finance
Item Type:Thesis (Masters)
Authors:Liu, Shurui
Institution:Concordia University
Degree Name:M. Sc.
Program:Finance
Date:October 2024
Thesis Supervisor(s):Walker, Thomas
Keywords:Natural Disasters, Political Connections, Chinese Stock Market, Event Study, Abnormal Returns, Cross-Sectional Analysis
ID Code:994726
Deposited By: Shurui Liu
Deposited On:17 Jun 2025 17:40
Last Modified:17 Jun 2025 17:40
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