Predicting financial markets with Google Trends and not so random keywords
Damien Challet and
Ahmed Bel Hadj Ayed
Papers from arXiv.org
Abstract:
We 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)
Date: 2013-07, Revised 2014-03
New Economics Papers: this item is included in nep-fmk and nep-for
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Working Paper: Predicting financial markets with Google Trends and not so random keywords (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1307.4643
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