Artikel

A principal component-guided sparse regression approach for the determination of bitcoin returns

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.

Language: Englisch

Bibliographic citation: Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 2 ; Pages: 1-10 ; Basel: MDPI

Classification: Wirtschaft

Subject: bitcoin
bubble
cryptocurrency
flexible least squares
LASSO
PC-LASSO
principal component
sparse regression

Event: Geistige Schöpfung

(who): Panagiōtidēs, Theodōros
Stengos, Thanasēs
Vravosinos, Orestis

Event: Veröffentlichung

(who): MDPI

(where): Basel

(when): 2020

DOI: doi:10.3390/jrfm13020033

Handle: http://hdl.handle.net/10419/239110

Last update: 10.03.2025, 11:41 AM CET

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Artikel

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Panagiōtidēs, Theodōros
Stengos, Thanasēs
Vravosinos, Orestis
MDPI

Time of origin

2020

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A principal component-guided sparse regression approach for the determination of bitcoin returns

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Other Objects (12)

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