新冠肺炎疫情對台灣產業股價指數影響之研究

The Impact of COVID-19 on The Stock Index of Various Industries in Taiwan

蔡淳妮(Chun-Ni Tsai)

指導教授 ： 唐代彪

國立臺灣大學/社會科學院/國家發展研究所/碩士(2021年)

https://doi.org/10.6342/NTU202200067

摘要

本文探討新冠肺炎疫情對台灣各產業股價指數之影響，分別使用單根檢定、共整合檢定以及多重分量迴歸模型進行實證分析。實證結果表明，不同分位數每日新病例數成長率與不同分位數之股價指數報酬率下，新冠肺炎疫情對產業股價指數的影響存在很大差異。不同產業所受到疫情的影響也相當不同，負面影響較大的產業類：航運類、觀光類、化學類、電器電纜類、油電燃氣類，而塑膠類產業只出現正向顯著影響，其餘產業類別及台股加權指數在不同條件分量下則是有正向顯著亦有負向顯著影響之結果出現。此外，我們發現當台灣新冠肺炎疫情病例數成長率位於50至75百分位時，其對於各個產業股價指數之影響相對較為顯著。

關鍵字

新冠疫情 ； 產業股價指數 ； 多重分量迴歸模型

並列摘要

In this study, we explore the impact of COVID-19 on the stock index of various industries in Taiwan by using ADF test, Johansen cointegration test and Quantile-on-Quantile regression (QQ). The empirical results show that the impact of COVID-19 on each stock index is different in different quantiles. Under 5% significant level, the regressors of shipping industry, tourism industry, chemical industry, oil and gas industry are negative in all quantile. The regressors of plastics industry are almost positive. The other industries and Taiwan Capitalization Weighted Stock Index have both positive and negative significant effects in different quantiles. Furthermore, we found that when the growth rate of COVID-19 cases in Taiwan is in the 50th to 75th percentile, its impact on the stock index of all industries is relatively significant.

並列關鍵字

COVID-19 ； Industrial stock index ； Quantile-on-Quantile regression

參考文獻

英文文獻

Baek, S., Mohanty, S. K., Glambosky, M. (2020). COVID-19 and stock market volatility: An industry level analysis. Finance Research Letters, 37, 101748.

Bouri, E., Gupta, R., Tiwari, A. K., Roubaud, D. (2017). Does Bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 23, 87-95.

Chen, C.-D., Chen, C.-C., Tang, W.-W., Huang, B.-Y. (2009). The positive and negative impacts of the SARS outbreak: A case of the Taiwan industries. The Journal of Developing Areas, 281-293.

Dickey, D. A., Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a), 427-431.