Analysis of Bitcoin Prices Using Market and Sentiment Variables

The World Economy, 2020

34 Pages Posted: 3 Nov 2020

See all articles by Burcu Kapar

Burcu Kapar

American University in Dubai

Jose Olmo

Universidad de Zaragoza; University of Southampton

Date Written: September 13, 2020


This paper proposes an empirical model for analyzing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010-2017 and 2010-2019. Price discovery is achieved through the Gonzalo-Granger permanent-transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin, and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalized by individuals’ search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018-2019 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.

Keywords: Bitcoin Price, Co-Integration, Cryptocurrency, Factor Models, Permanent Transitory Decomposition

JEL Classification: G00

Suggested Citation

KAPAR, BURCU and Olmo, Jose, Analysis of Bitcoin Prices Using Market and Sentiment Variables (September 13, 2020). The World Economy, 2020, Available at SSRN: or

BURCU KAPAR (Contact Author)

American University in Dubai ( email )

Dubai, UAE 28282
United Arab Emirates

Jose Olmo

Universidad de Zaragoza ( email )

Gran Via, 2
50005 Zaragoza, Zaragoza 50005

University of Southampton ( email )

United Kingdom

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