Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/147544
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dc.titlePROFITABILITY OF TRADING STRATEGIES BASED ON GOOGLE TRENDS
dc.contributor.authorCHIA KEAT LOONG
dc.date.accessioned2018-09-24T07:15:55Z
dc.date.available2018-09-24T07:15:55Z
dc.date.issued2017
dc.identifier.citationCHIA KEAT LOONG (2017). PROFITABILITY OF TRADING STRATEGIES BASED ON GOOGLE TRENDS. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/147544
dc.description.abstractThis paper seeks to explore the usefulness of data from Google Trends in identifying groups of stocks which may outperform the market. Using Google Trends data as a means for sorting stocks into quintiles weekly, I find that stocks in the lower quintiles have better performances after accounting for the popular Fama French factors. Tests that I have carried out suggest that this could potentially be attributed to the perceived risks by investors on stocks which they have insufficient information on. A back-testing strategy on the lower quintiles modestly outperforms the market after accounting for transaction costs and hindsight bias. However, I find that the results are not stable across time, raising doubts over the long term potential of utilizing Google Trends data for portfolio formation.
dc.subjectGoogle Trends, Stock Markets, Information Risk
dc.typeThesis
dc.contributor.departmentNUS Business School
dc.contributor.supervisorFONG WAI MUN
dc.contributor.supervisorKO CHIU YU
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF BUSINESS ADMINISTRATION WITH HONOURS
Appears in Collections:Bachelor's Theses

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