本研究利用ARMA(m,n)-GARCH(p,q)模型,探討COVID-19累積確診數與累積死亡數在不同觀察頻率下(5分鐘、10分鐘、30分鐘、60分鐘及日資料)對於指數波動性的影響。主要選擇的股價指數包括:臺灣加權指數、香港恒生指數、中國上證指數、日本日經225指數、韓國綜合股價指數、美國道瓊工業指數、英國富時100指數、法國CAC40指數、德國DAX指數以及義大利富時MIB指數等,並以2020年1月2日至2021年6月30日為研究期間。實證結果顯示累積確診數及累積死亡數對股市的波動性皆有顯著影響。由於病毒具有高度突變特性,在疫情不能有效控制的情況下,投資人仍須重視累積確診數與累積死亡數等數據的變化,以正確做出投資決策。
This study uses the ARMA(m,n)-GARCH(p,q) model to explore the impact of the January 2 to June 30, 2,020 on the Taiwan Weighted Index, Hang Seng Index, Shanghai Composite Index, Nikkei 225 Index, Korea Composite Index, Dow Jones Industrial Index, FTSE 100 Index, CAC 40 Index, DAX Index, FTSE MIB Index, the impact of COVID-19 cumulative number of confirmations and the cumulative number of deaths under different observation frequencies (5 minutes, 10 minutes, 30 minutes, 60 minutes, and daily data) on the volatility of the index. The empirical results show that both the cumulative number of confirmed cases and the cumulative number of deaths have a significant impact on the volatility of the stock market. Due to the highly mutable nature of the virus, investors should still pay attention to the changes in the cumulative number of confirmed cases and cumulative number of deaths in order to make proper investment decisions in the event that the outbreak cannot be effectively controlled.