Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71419
Title: Panic of COVID-19 on the volatility of U.S. portfolios: Applied big data from Google trend
Authors: Asama Liammukda
Manad Khamkong
Lampang Saenchan
Napon Hongsakulvasu
Authors: Asama Liammukda
Manad Khamkong
Lampang Saenchan
Napon Hongsakulvasu
Keywords: Computer Science;Decision Sciences
Issue Date: 25-Sep-2020
Abstract: © 2020 IEEE. In this study, we used the trend of COVID-19 from Google trend to represent a panic of investors in COVID-19 and measure the effect of that panic on time-varying volatility of U.S. portfolios by using Fama - French five factor models with GARCH model. The result of analysis, we can capture a time-varying volatility of all portfolios since 11/1/2019 to 4/30/2020 and trend of COVID-19 has affecting on time-varying volatility of the small neutral portfolio, big neutral portfolio, and small growth portfolio. The results of this study coincide with the event that investors panicked that caused a circuit breaker in the stock market. So, we can use Google trend for 'warning sign' of a COVID-19 panic.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097331646&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/71419
Appears in Collections:CMUL: Journal Articles

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