Abstract
We show the advantage of using Google search engine trends to forecast the volatility of the shortterm (weekly) exchange rate between the Mexican peso and United States dollar. We perform a comparison of models in the literature that have used Google Trends to examine explanatory variables. Some of
the models are based on time series, whereas others are based on the similarity function, which captures the cognitive form of human reasoning. For example, an investor who needs to know the value that a variable will take in the future will take into account relevant, known, and available information, and weigh it to calculate the forecast. We conclude that taking into account the Google Trends variable helps explains partially the behaviour of volatility; and it is necessary to incorporate more aggregation levels. Moreover, to the best of our knowledge, literature on the subject of using Google Trends to explain relevant economic variables is relatively scarce.
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