Quantifying stock market trading behavior using Google trends: the Philippine case

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dc.contributor.advisorAlonzo, Ruperto P.
dc.contributor.authorUbaldo, Victor Cesar I.
dc.contributor.authorMendoza, Gabriel Antonio M.
dc.date.accessioned2024-11-12T06:37:04Z
dc.date.available2024-11-12T06:37:04Z
dc.date.issued2013-12
dc.description.abstractGoogle Trends compiles search query volume of search terms. We relate this to the financial market by hypothesizing that search query volume can be an indicator of investor uncertainty. We assume that investors search for more information in the Internet when they are most uncertain about the state of the market. Conversely, investors may search for less information when they are optimistic about the market. Thus search terms related to finance may precede decreases in stock prices, while low search query volume might precede increases in stock prices. Moreover, if search query volume can help predict the movement of stock market prices, then profits may be made. Using a hypothetical portfolio in a time range of January 2004 to August 2013, we perform a strategy consisting of weekly decisions based on whether search query volume has relatively increased or decreased: long positions are made when search volume has relatively increased, and short positions are made when search volume has relatively decreased. In an alternate strategy, we make no transaction instead of making short positions. Using search volume data from Google Trends of 89 finance-related terms and using the Philippine Stock Exchange index as a basis for transaction gains, we found that the term success best predicts the stock market. We also test for Granger causality, in which we propose ·that success Granger causes the Philippine Stock Exchange index.
dc.identifier.urihttps://selib.upd.edu.ph/etdir/handle/123456789/957
dc.language.isoen
dc.subjectGoogle Trends
dc.subjectsearch query volume
dc.subjectPhilippine Stock Exchange index
dc.subjectprofit
dc.subjectGranger causality
dc.subjectuncertainty
dc.subjectstock market
dc.subjectlong positions
dc.subjectfinance
dc.subjecteconophysics
dc.titleQuantifying stock market trading behavior using Google trends: the Philippine case
dc.typeThesis

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