Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices

14 Pages Posted: 18 May 2015 Last revised: 21 May 2015

See all articles by Ifigeneia Georgoula

Ifigeneia Georgoula

Athens University of Economics and Business

Demitrios Pournarakis

Athens University of Economics and Business - Department of Management Science and Technology

Christos Bilanakos

Athens University of Economics and Business - Department of Management Science and Technology

Dionisios Sotiropoulos

AUEB

George M. Giaglis

Athens University of Economics and Business

Date Written: May 17, 2015

Abstract

This paper uses time-series analysis to study the relationship between Bitcoin prices and fundamental economic variables, technological factors and measurements of collective mood derived from Twitter feeds. Sentiment analysis has been performed on a daily basis through the utilization of a state-of-the-art machine learning algorithm, namely Support Vector Machines (SVMs). A series of short-run regressions shows that the Twitter sentiment ratio is positively correlated with Bitcoin prices. The short-run analysis also reveals that the number of Wikipedia search queries (showing the degree of public interest in Bitcoins) and the hash rate (measuring the mining difficulty) have a positive effect on the price of Bitcoins. On the contrary, the value of Bitcoins is negatively affected by the exchange rate between the USD and the euro (which represents the general level of prices). A vector error-correction model is used to investigate the existence of long-term relationships between cointegrated variables. This kind of long-run analysis reveals that the Bitcoin price is positively associated with the number of Bitcoins in circulation (representing the total stock of money supply) and negatively associated with the Standard and Poor's 500 stock market index (which indicates the general state of the global economy).

Keywords: Bitcoins, error correction, machine learning, sentiment analysis

Suggested Citation

Georgoula, Ifigeneia and Pournarakis, Demitrios and Bilanakos, Christos and Sotiropoulos, Dionisios and Giaglis, George M., Using Time-Series and Sentiment Analysis to Detect the Determinants of Bitcoin Prices (May 17, 2015). Available at SSRN: https://ssrn.com/abstract=2607167 or http://dx.doi.org/10.2139/ssrn.2607167

Ifigeneia Georgoula (Contact Author)

Athens University of Economics and Business ( email )

76 Patission Street
Athens, 104 34
Greece

Demitrios Pournarakis

Athens University of Economics and Business - Department of Management Science and Technology ( email )

Athens GR-11362
Greece

Christos Bilanakos

Athens University of Economics and Business - Department of Management Science and Technology ( email )

Athens GR-11362
Greece

Dionisios Sotiropoulos

AUEB ( email )

76 Patission Street
Athens, 104 34
Greece

George M. Giaglis

Athens University of Economics and Business ( email )

Athens, 104 34

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