Manipulation Detection in the Bitcoin Market

Student: Iashchenko Anastasiia

Supervisor: Sylvain Carré

Faculty: International College of Economics and Finance

Educational Programme: Double degree programme in Economics of the NRU HSE and the University of London (Bachelor)

Year of Graduation: 2021

This paper is dedicated to the identification and characterization of orders aimed at manipulation of the Bitcoin market. The order book data from Bitfinex exchange was retrieved for the period of 30.10.2020——31.10.2020. To analyze it, Hidden Markov Model was used along with combination of Kernel Principal Component Analysis and Local Outlier Factor model. The models used variables describing price changes and market liquidity. Although the outputs of the models did not coincide completely, some features of manipulative trades were similar, such as high price and low market liquidity. Some manipulation strategies were also associated with large price changes per unit of time, which is 5 seconds in our case.

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