We study information dynamics between the largest Bitcoin exchange markets during the bubble in 2017–2018. By analyzing high-frequency market microstructure observables with different information-theoretic measures for dynamical systems, we find temporal changes in infor- mation sharing across markets. In particular, we study time-varying components of predictability, memory, and (a)synchronous coupling, measured by transfer entropy, active information storage, and multi-information. By comparing these empirical findings with several mod- els, we argue that some results could relate to intra-market and inter-market regime shifts and changes in the direction of information flow between different market observables.

Information dynamics of price and liquidity around the 2017 Bitcoin markets crash

Lillo, Fabrizio;
2022

Abstract

We study information dynamics between the largest Bitcoin exchange markets during the bubble in 2017–2018. By analyzing high-frequency market microstructure observables with different information-theoretic measures for dynamical systems, we find temporal changes in infor- mation sharing across markets. In particular, we study time-varying components of predictability, memory, and (a)synchronous coupling, measured by transfer entropy, active information storage, and multi-information. By comparing these empirical findings with several mod- els, we argue that some results could relate to intra-market and inter-market regime shifts and changes in the direction of information flow between different market observables.
2022
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Mutual information; behavior; models; flow
   Horizon 2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/128225
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