4.1 Article

Quantifying endogeneity of cryptocurrency markets

Journal

EUROPEAN JOURNAL OF FINANCE
Volume 28, Issue 7, Pages 784-799

Publisher

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/1351847X.2020.1791925

Keywords

Bitcoin; branching ratio; cryptocurrencies; endogeneity; Hawkes process; market reflexivity; trading behavior

Funding

  1. Swiss National Science Foundation [105218-179175]
  2. Charles University PRIMUS program [PRIMUS/19/HUM/17]
  3. SVV project [260 463]
  4. Swiss National Science Foundation (SNF) [105218_179175] Funding Source: Swiss National Science Foundation (SNF)

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This article constructs a 'reflexivity' index to measure the activity generated endogenously within a market for cryptocurrencies and analyzes high-frequency trading data using a Hawkes process. The study finds that the mid-price dynamics of Bitcoin exhibit long-memory properties and can be well explained by a power-law kernel.
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.

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