Predicting Financial Markets with Google Trends and Not so Random Keywords

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)

[1]  William N. Goetzmann,et al.  Survivorship Bias in Performance Studies , 1992 .

[2]  D FreemanJohn.  Behind the Smoke and Mirrors: Gauging the Integrity of Investment Simulations , 1992 .

[3]  Christopher R. Blake,et al.  Survivorship Bias and Mutual Fund Performance , 1995 .

[4]  G.E. Moore,et al.  Cramming More Components Onto Integrated Circuits , 1998, Proceedings of the IEEE.

[5]  H. White,et al.  Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap , 1999 .

[6]  Jonathan H. Wright,et al.  News and Noise in G-7 GDP Announcements , 2000 .

[7]  H. White,et al.  A Reality Check for Data Snooping , 2000 .

[8]  R. Gencay,et al.  An Introduc-tion to High-Frequency Finance , 2001 .

[9]  M. Marsili.  Dissecting financial markets: sectors and states , 2002, cond-mat/0207156.

[10]  Fabrice Bellard,et al.  QEMU, a Fast and Portable Dynamic Translator , 2005, USENIX ATC, FREENIX Track.

[11]  David J. Leinweber,et al.  Stupid Data Miner Tricks , 2007 .

[12]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[13]  Zhi Da,et al.  In Search of Attention , 2009 .

[14]  H. Varian,et al.  Predicting the Present with Google Trends , 2009 .

[15]  Jennifer L. Castle,et al.  Nowcasting is not Just Contemporaneous Forecasting , 2009, National Institute Economic Review.

[16]  M.H. Kryder,et al.  After Hard Drives—What Comes Next? , 2009, IEEE Transactions on Magnetics.

[17]  Zhi Da,et al.  In Search of Earnings Predictability , 2010 .

[18]  Stephen Berard,et al.  Implications of Historical Trends in the Electrical Efficiency of Computing , 2011, IEEE Annals of the History of Computing.

[19]  Michał Dzieliński,et al.  Measuring economic uncertainty and its impact on the stock market , 2012 .

[20]  Stephen J. Hardiman,et al.  Critical reflexivity in financial markets: a Hawkes process analysis , 2013, 1302.1405.

[21]  H. Stanley,et al.  Quantifying Trading Behavior in Financial Markets Using Google Trends , 2013, Scientific Reports.

[22]  H. Eugene Stanley,et al.  Quantifying Wikipedia Usage Patterns Before Stock Market Moves , 2013, Scientific Reports.