Hong Nguyen Thi Hoa, Huong Pham Thi Mai, Linh Nguyen Yen
Financial Management-Statistics Analysis Department, Faculty of Business Administration, Foreign Trade University, Postal address: 91 Chua Lang Street, Dong Da District, Ha Noi, Viet Nam.
School of Economics and International Business, Foreign Trade University, Postal address: 91 Chua Lang Street, Dong Da District, Ha Noi, Viet Nam.
Heliyon. 2023 Jul 25;9(8):e18665. doi: 10.1016/j.heliyon.2023.e18665. eCollection 2023 Aug.
This paper examines the impact of COVID-19 nationwide lockdown on the relationship between weather anomaly and the Vietnam stock market - a fast-growing emerging market. The paper employs event study methodology to compute the cumulative abnormal return of stocks during the pandemic, and the Holt-Winters Exponential Smoothing model to build the formula for weather anomaly for weather variables. In addition, a -test is performed to examine the statistical significance of weather variables, as well as the impact that the lockdown order had on stock performance. Cross-sectional analysis by Ordinary Least Squares regression is also applied for estimating the relationship between weather and stock market performance. The finding shows that prior to the COVID-19 lockdown, all of the risk and return indicators, with the exception of idiosyncratic risk, are affected by temperature. After the lockdown order was withdrawn, temperature is only correlated with cumulative real returns and cumulative abnormal returns. Meanwhile, air pressure only appears to have an influence on cumulative abnormal returns after the lockdown, yet being the only meteorological factor that could impact the stock market during the lockdown. Generally, the larger the weather anomaly, the worse the returns and the higher the risks. The paper gives recommendations for listed companies and authorities to have better performance while engaging in and regulating the stock markets. Moreover, the results can be used as a reference for the investing community to incorporate meteorological factors into their analysis.
本文考察了新冠疫情全国封锁对天气异常与越南股票市场（一个快速发展的新兴市场）之间关系的影响。本文采用事件研究方法来计算疫情期间股票的累积异常回报，并使用霍尔特-温特斯指数平滑模型来构建天气变量的天气异常公式。此外，还进行了t检验，以检验天气变量的统计显著性，以及封锁令对股票表现的影响。通过普通最小二乘法回归进行的横截面分析也被用于估计天气与股票市场表现之间的关系。研究结果表明，在新冠疫情封锁之前，除了特质风险外，所有风险和回报指标都受到温度的影响。在解除封锁令之后，温度仅与累积实际回报和累积异常回报相关。与此同时，气压似乎仅在封锁后对累积异常回报有影响，且是封锁期间唯一能够影响股票市场的气象因素。一般来说，天气异常越大，回报越差，风险越高。本文为上市公司和当局在参与和监管股票市场时取得更好表现提供了建议。此外，研究结果可为投资界在分析中纳入气象因素提供参考。
