Determining the Endogeneity of Markets for Cryptocurrencies
Dr. Michael Mark and Prof. Thomas Weber’s research on “Quantifying Endogeneity of Cryptocurrency Markets,” published in the current issue of the European Journal of Finance, examines the volatility of markets for cryptocurrencies, which is well-known to far exceed that of markets for traditional asset classes such as stocks and bonds. To investigate this, the authors determine the branching ratios associated with Bitcoin mid-price dynamics, when these are modeled using self-exciting point processes with different parametric kernels. They further address the issue of regime changes and the concomitant optimal length of an observation horizon for the validity of a model specification. The paper was co-authored with Jan Sila, a doctoral candidate in Finance and Capital Markets at Charles University, Prague.
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 a 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 the fiat-currency market
Acknowledgement: This research was funded by the Swiss National Science Foundation (grant no. 105218-179175).
Mark, M., Sila, J., Weber, T.A. (2022) “Quantifying Endogeneity of Cryptocurrency Markets,” European Journal of Finance, Vol. 28, No. 7, pp. 784—799.
[DOI: 10.1080/1351847X.2020.1791925; open access]