Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/147544
Title: PROFITABILITY OF TRADING STRATEGIES BASED ON GOOGLE TRENDS
Authors: CHIA KEAT LOONG
Keywords: Google Trends, Stock Markets, Information Risk
Issue Date: 2017
Citation: CHIA KEAT LOONG (2017). PROFITABILITY OF TRADING STRATEGIES BASED ON GOOGLE TRENDS. ScholarBank@NUS Repository.
Abstract: This 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.
URI: http://scholarbank.nus.edu.sg/handle/10635/147544
Appears in Collections:Bachelor's Theses (Restricted)

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