Which search terms perform best in a Google trading strategy?
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We’ve seen that more financially related words performed better in our trading strategy than less financially related words. However, Internet users search for many different topics online. Is financial relatedness the only important factor in determining whether a keyword will perform well in this strategy?
Chester Curme explains how he used an algorithm to read all of Wikipedia, and extract groups of words relating to a wide range of different topics, such as education, sports, food, business and politics. He describes an analysis designed to find out which words were searched for before stock market falls. His results suggest financial relatedness is not the only dimension of interest.
Chester Curme has a PhD in Physics from Boston University and previously worked as a research fellow at the Data Science Lab at Warwick Business School. His research interests lie in interdisciplinary applications of statistical physics to problems in economics, computational social science, and network science. His work has been featured in both TV appearances and articles throughout the worldwide press, including the Financial Times, Washington Post, Wired, and Forbes.
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Big Data: Measuring And Predicting Human Behaviour
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