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

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Listed:
  • Thanasis Stengos

    (Department of Economics and Finance, University of Guelph, Guelph ON Canada)

  • Theodore Panagiotidis

    (Department of Economics, University of Macedonia)

  • Orestis Vravosinos

    (Department of Economics, New York University)

Abstract

We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010–2018 (2,872 daily observations). The principal component-guided sparse regression is employed, introduced by Tay et al. (2018). 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.

Suggested Citation

  • Thanasis Stengos & Theodore Panagiotidis & Orestis Vravosinos, 2020. "A principal component-guided sparse regression approach for the determination of bitcoin returns," Working Papers 2001, University of Guelph, Department of Economics and Finance.
    • Handle: RePEc:gue:guelph:2020-01
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    References listed on IDEAS

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    15. Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019. "The effects of markets, uncertainty and search intensity on bitcoin returns," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
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    Cited by:

    1. Emon Kalyan Chowdhury & Mohammad Nayeem Abdullah, 2024. "Gauging Demand for Cryptocurrency over the Economic Policy Uncertainty and Stock Market Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 37-55, July.
    2. Thanasis Stengos, 2021. "Recent Developments in Cryptocurrency Markets: Co-Movements, Spillovers and Forecasting," JRFM, MDPI, vol. 14(3), pages 1-3, February.
    3. Pınar Kaya Soylu & Mustafa Okur & Özgür Çatıkkaş & Z. Ayca Altintig, 2020. "Long Memory in the Volatility of Selected Cryptocurrencies: Bitcoin, Ethereum and Ripple," JRFM, MDPI, vol. 13(6), pages 1-21, May.
    4. Nikolaos A. Kyriazis, 2020. "Is Bitcoin Similar to Gold? An Integrated Overview of Empirical Findings," JRFM, MDPI, vol. 13(5), pages 1-19, May.
    5. Mokni, Khaled & Youssef, Manel & Ajmi, Ahdi Noomen, 2022. "COVID-19 pandemic and economic policy uncertainty: The first test on the hedging and safe haven properties of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 60(C).
    6. Adel Benhamed & Ahlem Selma Messai & Ghassen El Montasser, 2023. "On the Determinants of Bitcoin Returns and Volatility: What We Get from Gets?," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    7. Umar, Muhammad & Su, Chi-Wei & Rizvi, Syed Kumail Abbas & Shao, Xue-Feng, 2021. "Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US?," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Pinar Deniz & Thanasis Stengos, 2020. "Cryptocurrency Returns before and after the Introduction of Bitcoin Futures," JRFM, MDPI, vol. 13(6), pages 1-21, June.
    9. Zvonko Merkaš & Vlasta Roška, 2021. "The Impact of Unsystematic Factors on Bitcoin Value," JRFM, MDPI, vol. 14(11), pages 1-17, November.
    10. Mokni, Khaled & Ajmi, Ahdi Noomen & Bouri, Elie & Vo, Xuan Vinh, 2020. "Economic policy uncertainty and the Bitcoin-US stock nexus," Journal of Multinational Financial Management, Elsevier, vol. 57.
    11. Serda Selin Ozturk, 2020. "Dynamic Connectedness between Bitcoin, Gold, and Crude Oil Volatilities and Returns," JRFM, MDPI, vol. 13(11), pages 1-14, November.

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    More about this item

    Keywords

    bitcoin; cryptocurrency; bubble; sparse regression; LASSO; PC-LASSO; principal component; flexible least squares;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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    This paper has been announced in the following NEP Reports:

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