A Principal Component-Guided Sparse Regression Approach for the Determination of Bitcoin Returns

Theodore Panagiotidis, Thanasis Stengos and Orestis Vravosinos

JRFM, 2020, vol. 13, issue 2, 1-10

Abstract: We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010–2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among the most important variables for bitcoin. We also trace strong evidence of bubbly bitcoin behavior in the 2017–2018 period.

Keywords: bitcoin; cryptocurrency; bubble; sparse regression; LASSO; PC-LASSO; principal component; flexible least squares (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (11)

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Working Paper: A principal component-guided sparse regression approach for the determination of bitcoin returns (2020)
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