Do Google Trend Data Contain More Predictability than Price Returns?

15 Pages Posted: 8 Mar 2014

See all articles by Damien Challet

Damien Challet

CentraleSupélec; Encelade Capital SA

Ahmed Bel Hadj Ayed

BNP Paribas; Ecole Centrale Paris - Laboratory of Mathematics Applied to Systems

Date Written: March 7, 2014

Abstract

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.

Keywords: Google Trends, prediction, backtest, trading strategy

JEL Classification: G12, G14

Suggested Citation

Challet, Damien and Bel Hadj Ayed, Ahmed, Do Google Trend Data Contain More Predictability than Price Returns? (March 7, 2014). Available at SSRN: https://ssrn.com/abstract=2405804 or http://dx.doi.org/10.2139/ssrn.2405804

Damien Challet (Contact Author)

CentraleSupélec ( email )

Labo MICS
3, rue Joliot-Curie
Gif-sur-Yvette, 91192
France

Encelade Capital SA ( email )

Chemin du Bochet 8
Sulpice, 1025
Switzerland

Ahmed Bel Hadj Ayed

BNP Paribas ( email )

Paris
France

Ecole Centrale Paris - Laboratory of Mathematics Applied to Systems ( email )

Grande Voie des Vignes
Châtenay-Malabry, 92290
France

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