The Dynamics of Returns Predictability in Cryptocurrency Markets

50 Pages Posted: 30 May 2020 Last revised: 5 May 2022

See all articles by Daniele Bianchi

Daniele Bianchi

School of Economics and Finance, Queen Mary University of London

Massimo Guidolin

University of Liverpool Management School; Bocconi University - CAREFIN - Centre for Applied Research in Finance

Manuela Pedio

University of Bristol; Bocconi University - CAREFIN - Centre for Applied Research in Finance

Date Written: May 1, 2020

Abstract

In this paper, we take a forecasting perspective and compare the information content of a set of market risk factors, cryptocurrency-specific predictors, and sentiment variables for the returns of cryptocurrencies vs traditional asset classes. To this aim, we rely on a flexible dynamic econometric model that not only features time-varying coefficients, but also allows for the entire forecasting model to change over time to capture the time variation in the exposures of major digital currencies to the predictive variables. Besides, we investigate whether the inclusion of cryptocurrencies in an already diversified portfolio leads to additional economic gains. The main empirical results suggest that cryptocurrencies are not systematically predicted by stock market factors, precious metal commodities or supply factors. On the contrary, they display a time-varying but significant exposure to investors' attention. In addition, also because of a lack of predictability compared to traditional asset classes, cryptocurrencies lead to realized expected utility gains for a power utility investor.

Keywords: Bitcoin, cryptocurrencies, returns predictability, investments, dynamic model averaging.

JEL Classification: G11, G12, G17

Suggested Citation

Bianchi, Daniele and Guidolin, Massimo and Pedio, Manuela, The Dynamics of Returns Predictability in Cryptocurrency Markets (May 1, 2020). BAFFI CAREFIN Centre Research Paper No. 2020-143, Available at SSRN: https://ssrn.com/abstract=3609949 or http://dx.doi.org/10.2139/ssrn.3609949

Daniele Bianchi

School of Economics and Finance, Queen Mary University of London ( email )

Mile End Road
London, London E1 4NS
United Kingdom

HOME PAGE: http://whitesphd.com

Massimo Guidolin (Contact Author)

University of Liverpool Management School ( email )

Bocconi University - CAREFIN - Centre for Applied Research in Finance

Via Sarfatti 25
Milan, 20136
Italy

Manuela Pedio

University of Bristol ( email )

University of Bristol,
Senate House, Tyndall Avenue
Bristol, BS8 ITH
United Kingdom

Bocconi University - CAREFIN - Centre for Applied Research in Finance ( email )

Via Sarfatti, 25
Milan, 20136
Italy

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