Quantifying endogeneity of cryptocurrency markets

Michael Mark, Jan Sila and Thomas Weber

The European Journal of Finance, 2022, vol. 28, issue 7, 784-799

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.

Date: 2022
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Working Paper: Quantifying Endogeneity of Cryptocurrency Markets (2019)
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DOI: 10.1080/1351847X.2020.1791925

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