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Quantifying endogeneity of cryptocurrency markets

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  • Michael Mark
  • Jan Sila
  • Thomas A. Weber

Abstract

We construct a ‘reflexivity’ index to measure the activity generated endogenously within a market for cryptocurrencies. For this purpose, we fit a univariate self-exciting Hawkes process with two classes of parametric kernels to high-frequency trading data. A parsimonious model of both endogenous and exogenous dynamics enables a direct comparison with exchanges for traditional asset classes, in terms of identified branching ratios. We also formulate a ‘Hawkes disorder problem,’ as generalization of the established Poisson disorder problem, and provide a simulation-based approach to determining an optimal observation horizon. Our analysis suggests that Bitcoin mid-price dynamics feature long-memory properties, well explained by the power-law kernel, at a level of criticality similar to fiat-currency markets.

Suggested Citation

  • Michael Mark & Jan Sila & Thomas A. Weber, 2022. "Quantifying endogeneity of cryptocurrency markets," The European Journal of Finance, Taylor & Francis Journals, vol. 28(7), pages 784-799, May.
    • Handle: RePEc:taf:eurjfi:v:28:y:2022:i:7:p:784-799
    DOI: 10.1080/1351847X.2020.1791925
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    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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