Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/71419
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dc.contributor.authorAsama Liammukdaen_US
dc.contributor.authorManad Khamkongen_US
dc.contributor.authorLampang Saenchanen_US
dc.contributor.authorNapon Hongsakulvasuen_US
dc.date.accessioned2021-01-27T03:44:44Z-
dc.date.available2021-01-27T03:44:44Z-
dc.date.issued2020-09-25en_US
dc.identifier.other2-s2.0-85097331646en_US
dc.identifier.other10.1109/IBDAP50342.2020.9245613en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85097331646&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/71419-
dc.description.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.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.titlePanic of COVID-19 on the volatility of U.S. portfolios: Applied big data from Google trenden_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2020 1st International Conference on Big Data Analytics and Practices, IBDAP 2020en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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