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Bubble regime identification in an attention-based model for Bitcoin and Ethereum price dynamics

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  • Cretarola, Alessandra
  • Figà-Talamanca, Gianna

Abstract

In this paper we extend the model in Cretarola, Figà-Talamanca, “Detecting bubbles in Bitcoin price dynamics via market exuberance”, Annals of Operations Research (2019), by allowing for a state-dependent correlation parameter between asset returns and market attention. We assume that the change of state is described by a continuous time latent Markov chain and we propose an estimation procedure based on the conditional maximum likelihood and on the Hamilton filter. Finally, model parameters, as well as Markov chain transition probabilities, are estimated on Bitcoin and Ethereum returns in case market attention is measured via the Google Search Volume Index for the keywords “bitcoin” and “ethereum”, respectively; up to four regimes are considered in the empirical application. The empirical outcomes show that the model is not only capable of identifying bubble and non-bubble regimes but also enables the interpretation of the correlation between cryptocurrencies and their market attention as a tuning to define the speed at which a bubble boosts.

Suggested Citation

  • Cretarola, Alessandra & Figà-Talamanca, Gianna, 2020. "Bubble regime identification in an attention-based model for Bitcoin and Ethereum price dynamics," Economics Letters, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:ecolet:v:191:y:2020:i:c:s0165176519304203
    DOI: 10.1016/j.econlet.2019.108831
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    References listed on IDEAS

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    Cited by:

    1. Alessandra Cretarola & Gianna Figà-Talamanca & Cyril Grunspan, 2021. "Blockchain and cryptocurrencies: economic and financial research," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 781-787, December.
    2. Alessandra Cretarola & Benedetta Salterini, 2023. "Utility-based indifference pricing of pure endowments in a Markov-modulated market model," Papers 2301.13575, arXiv.org.
    3. Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    4. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    5. Urquhart, Andrew, 2022. "Under the hood of the Ethereum blockchain," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
    7. Katia Colaneri & Alessandra Cretarola & Benedetta Salterini, 2021. "Optimal Investment and Proportional Reinsurance in a Regime-Switching Market Model under Forward Preferences," Mathematics, MDPI, vol. 9(14), pages 1-27, July.
    8. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    9. Li, Yi & Zhang, Wei & Urquhart, Andrew & Wang, Pengfei, 2022. "The role of media coverage in the bubble formation: Evidence from the Bitcoin market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    10. Zhang, Shuai & Hou, Xinyu & Ba, Shusong, 2021. "What determines interest rates for bitcoin lending?," Research in International Business and Finance, Elsevier, vol. 58(C).
    11. Agosto, Arianna & Cerchiello, Paola & Pagnottoni, Paolo, 2022. "Sentiment, Google queries and explosivity in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

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    More about this item

    Keywords

    Bitcoin; Ethereum; Regime-switching model; Bubble;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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