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Quantifying Endogeneity of Cryptocurrency Markets

Author

Listed:
  • Michael Mark

    (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland)

  • Jan Sila

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Opletalova 26, 110 00, Prague, Czech Republic)

  • Thomas A. Weber

    (Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland)

Abstract

In this paper we construct a "reflexivity" index for Bitcoin crypto currency that measures the amount of activity generated endogenously within the market. For this purpose we fit a univariate self-exciting Hawkes process with two-classes of parametric kernels to high-frequency trade data that allows for a parsimonious representation of endogenous-exogenous dynamics.

Suggested Citation

  • Michael Mark & Jan Sila & Thomas A. Weber, 2019. "Quantifying Endogeneity of Cryptocurrency Markets," Working Papers IES 2019/29, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2019.
    • Handle: RePEc:fau:wpaper:wp2019_29
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    File URL: http://ies.fsv.cuni.cz/sci/publication/show/id/6144/lang/cs
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    Keywords

    Hawkes process; endogeneity; branching ratio; maximum-likelihood estimation; cryptocurrencies; bitcoin;
    All these keywords.

    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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