EconPapers    
Economics at your fingertips  
 

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

Johannes Bleher and Thomas Dimpfl

International Review of Financial Analysis, 2019, vol. 63, issue C, 147-159

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.

Keywords: Bitcoin; Cryptocurrency; Volatility; Prediction; Google search volume (search for similar items in EconPapers)
JEL-codes: C22 C43 C53 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1057521918304198
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:63:y:2019:i:c:p:147-159

DOI: 10.1016/j.irfa.2019.03.003

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:finana:v:63:y:2019:i:c:p:147-159