Today I Got a Million, Tomorrow, I Don't Know: On the Predictability of Cryptocurrencies by Means of Google Search Volume

34 Pages Posted: 28 Feb 2018 Last revised: 27 Mar 2019

See all articles by Johannes Bleher

Johannes Bleher

University of Tuebingen - Department of Statistics and Econometrics

Thomas Dimpfl

University of Tuebingen - Department of Statistics and Econometrics

Date Written: February 19, 2018

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 mulit-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 holds 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.

Keywords: Bitcoin, Cryptocurrency, Volatility, Prediction, Google Search Volume

JEL Classification: C22, C43, C53

Suggested Citation

Bleher, Johannes and Dimpfl, Thomas, Today I Got a Million, Tomorrow, I Don't Know: On the Predictability of Cryptocurrencies by Means of Google Search Volume (February 19, 2018). Available at SSRN: https://ssrn.com/abstract=3126324 or http://dx.doi.org/10.2139/ssrn.3126324

Johannes Bleher (Contact Author)

University of Tuebingen - Department of Statistics and Econometrics ( email )

Germany

Thomas Dimpfl

University of Tuebingen - Department of Statistics and Econometrics ( email )

Germany

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
245
Abstract Views
1,329
rank
141,282
PlumX Metrics