Quantifying Endogeneity of Cryptocurrency Markets

Michael Mark, Jan Sila and Thomas Weber
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Michael Mark: Chair of Operations, Economics and Strategy, Ecole Polytechnique Federale de Lausanne, Station 5, CH-1015 Lausanne, Switzerland

No 2019/29, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

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.

Keywords: Hawkes process; endogeneity; branching ratio; maximum-likelihood estimation; cryptocurrencies; bitcoin (search for similar items in EconPapers)
JEL-codes: C58 G14 G15 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2019-10, Revised 2019-10
New Economics Papers: this item is included in nep-ore and nep-pay
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Journal Article: Quantifying endogeneity of cryptocurrency markets (2022)
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