domain using semantic vectors. Then, we train a linear regression model to predict the volatility of a future week using as input google trends data for those keywords in the previous week. 2 Related Work Past work on predicting market trends has shed some light on the usefulness of social data. Some

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After this, we added the Google Trends data as an external regressor and identified the SARIMA (0,1,1) (0,1,1) [52] model as optimal. We made predictions for the validation interval using these two models and compared predictions with the values of the validation data set.

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Issues with Google Trends Mixed frequency: Trends is available daily/weekly basis while series of interest may be weekly or monthly. (This is a plus.) Google Trends is an index: normalized query share using broad match Must have at least 50 observations to appear in Google Trends due to privacy policy. Google Trends is sampled data, and changes.

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