Inferring short-term volatility indicators from Bitcoin blockchain

Nino Antulov-Fantulin, Dijana Tolic, Matija Piskorec, Zhang Ce and Irena Vodenska

Papers from arXiv.org

Abstract: In this paper, we study the possibility of inferring early warning indicators (EWIs) for periods of extreme bitcoin price volatility using features obtained from Bitcoin daily transaction graphs. We infer the low-dimensional representations of transaction graphs in the time period from 2012 to 2017 using Bitcoin blockchain, and demonstrate how these representations can be used to predict extreme price volatility events. Our EWI, which is obtained with a non-negative decomposition, contains more predictive information than those obtained with singular value decomposition or scalar value of the total Bitcoin transaction volume.

Date: 2018-09
New Economics Papers: this item is included in nep-pay and nep-rmg
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Published in 7th International Conference on Complex Networks and their Applications 2018

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1809.07856

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