Do Google Trend Data Contain More Predictability than Price Returns?
- Damien Challet and Ahmed Bel Hadj Ayed
- A version of the paper can be found here.
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Using non-linear machine learning methods and a proper backtest procedure, we critically examine the claim that Google Trends can predict future price returns. We first review the many potential biases that may influence backtests with this kind of data positively, the choice of keywords being by far the greatest culprit. We then argue that the real question is whether such data contain more predictability than price returns themselves: our backtest yields a performance of about 17bps per week which only weakly depends on the kind of data on which predictors are based, i.e. either past price returns or Google Trends data, or both.
Google Trends Data
Quote from the paper:
We therefore conclude that price returns and GT contain about the same amount of predictive information, at least with the methods we have used and challenge to community to do any better.
First, a look at different keywords and their ability to predict SP 500 returns. Clearly, there is some evidence for data-mining in the “Google predicts returns” literature.
Google Trends Data Needs Some Work!
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