A Bayesian approach for the determinants of bitcoin returns

Thanasis Stengos, Theodore Panagiotidis and Georgios Papapanagiotou

No 2302, Working Papers from University of Guelph, Department of Economics and Finance

Abstract: This paper examines the effect of thirty-one variables on bitcoin returns over the period 2015-2021. We use a Bayesian LASSO model that accounts for stochastic volatility and leverage effect. We examine the impact of economic, financial and technological variables as well as uncertainty and attention indicators on bitcoin returns. Furthermore, we consider two recently proposed indicators (Central Bank Digital Currency (CBDC)) for uncertainty and attention. Our findings suggest that sentiment and technological factors have the most profound effect on bitcoin returns. Regarding economic/financial variables, stock market returns and volatility indices have the greatest impact on bitcoin returns.

Keywords: Bitcoin; Cryptocurrency; LASSO; Bayesian; CBDC. (search for similar items in EconPapers)
JEL-codes: C11 D80 G12 G15 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2023
New Economics Papers: this item is included in nep-ban, nep-fdg, nep-mon and nep-pay
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Related works:
Journal Article: A Bayesian approach for the determinants of bitcoin returns (2024)
Working Paper: A Bayesian approach for the determinants of bitcoin returns (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:gue:guelph:2023-02

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