Measuring COVID-19 Effects on World and National Stock Market Returns

被引:10
|
作者
Khan Thavit, Anya [1 ]
机构
[1] Thammasat Univ, Fac Commerce & Accountancy, Finance & Banking, 2 Phra Chan Rd, Bangkok 10200, Thailand
来源
关键词
Kalman Filtering; New Normal; Pandemic; Return Behavior; IMPACT; VOLATILITY;
D O I
10.13106/jafeb.2021.vol8.no2.0001
中图分类号
F [经济];
学科分类号
02 ;
摘要
Previous studies have found the significant adverse effects of coronavirus disease 2019 (COVID-19) on stock returns and volatility. The effects varied with the confirmed cases and deaths. However, the extent of the effects have never been measured exactly. This study proposes a measurement model for the COVID-19 effects. In the proposed model, stock returns in the COVID-19 period are weighted averages of pre-COVID-19 normal returns and COVID-19-induced returns. The effects are measured by the contributing weights of the COVID-19-induced returns. Kalman filtering is used to estimate the model for the world and Chinese markets, in combination with 10 markets - five most affected countries (United States, India, Brazil, Russia, and France) and five best recovering countries (Hong Kong, Australia, Singapore, Thailand, and South Korea). The sample returns are daily, obtained from the closing Morgan Stanley global investable market indexes. The full period is from September 24, 2018, to October 30, 2020, whereas the COVID-19 period is from November 18, 2019, to October 30, 2020. The contributing weights are significant and close to 100% for all markets. The COVID-19-induced returns replace the pre-COVID-19 normal returns; they are negatively auto-correlated and highly volatile. The COVID-19-induced returns are new normal returns in the COVID-19 period.
引用
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页码:1 / 13
页数:13
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