Predicting financial markets with Google Trends and not so random keywords
AbstractWe check the claims that data from Google Trends contain enough data to predict future financial index returns. We first discuss the many subtle (and less subtle) biases that may affect the backtest of a trading strategy, particularly when based on such data. Expectedly, the choice of keywords is crucial: by using an industry-grade backtesting system, we verify that random finance-related keywords do not to contain more exploitable predictive information than random keywords related to illnesses, classic cars and arcade games. We however show that other keywords applied on suitable assets yield robustly profitable strategies, thereby confirming the intuition of Preis et al. (2013)
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1307.4643.
Date of creation: Jul 2013
Date of revision: Mar 2014
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-07-20 (All new papers)
- NEP-FMK-2013-07-20 (Financial Markets)
- NEP-FOR-2013-07-20 (Forecasting)
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