Our team conducted a 15-week regression analysis in which we observed whether or not Google Search Volume (GSV) can serve as an explanatory variable for stock market returns, in particular, for the New York Stock Exchange (NYSE). The study attempts to provide quantitative evidence that the Efficient Market Hypothesis, which states that stock market returns cannot be explained with factual evidence, is false. The group researched the fundamentals behind stock market swings, as well as the cause for various movements in Google Trends. Through running Microsoft Excel regressions on these two sets of data, we can conclude that there is a positive correlation between search terms on GSV and the NYSE. That is, one has the potential to predict various stock index results based on GSV trends.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Lamb, Jason Stuart
• Thulin, Steven William
• Murtagh, Brian Kerry
• DellaPorta, Chad Daniel

Subject

• Industry
• Computing

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-101116-112300

Keyword

• Data mining
• Stock exchanges
• Marketing

Advisor

• Koutmos, Dimitrios

Year

• 2016

Date created

• 2016-10-11

Location

• Worcester

Resource type

• Interactive Qualifying Project

Rights statement

• In Copyright