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Information dynamics of price and liquidity around the 2017 Bitcoin markets crash
2022
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 information 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
doi:10.1063/5.0080462
pmid:35489840
fatcat:45yfsy2fmjfodk5nhefrmdyb3i