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Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume

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  • Bleher, Johannes
  • Dimpfl, Thomas

Abstract

We evaluate the usefulness of Google search volume to predict returns and volatility of multiple cryptocurrencies. The analysis is based on a new algorithm which allows to construct multi-annual, consistent time series of Google search volume indices (SVIs) on various frequencies. As cryptocurrencies are actively traded on a continuous basis and react very fast to new information, we conduct the analysis initially on a daily basis, lifting the data imposed restriction faced by previous research. In line with the literature on financial markets, we find that returns are not predictable while volatility is predictable to some extent. We discuss a number of reasons why the predictive power is poor. One aspect is the observational frequency which is therefore varied. The results of unpredictable cryptocurrency returns hold on higher (hourly) and lower (weekly) frequencies. Volatility, in contrast, is predictable on all frequencies and we document an increasing accuracy of the forecast when the sampling frequency is lowered.

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  • Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
    • Handle: RePEc:eee:finana:v:63:y:2019:i:c:p:147-159
    DOI: 10.1016/j.irfa.2019.03.003
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    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Volatility; Prediction; Google search volume;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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