Bitcoin market return and volatility forecasting using transaction network flow properties

Steve Y. Yang, Jinhyoung Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

Bit coin, as the foundation for a secure electronic payment system, has drawn broad interests from researchers in recent years. In this paper, we analyze a comprehensive Bit coin transaction dataset and investigate the interrelationship between the flow of Bit coin transactions and its price movement. Using network theory, we examine a few complexity measures of the Bit coin transaction flow networks, and we model the joint dynamic relationship between these complexity measures and Bit coin market variables such as return and volatility. We find that a particular complexity measure of the Bit coin transaction network flow is significantly correlated with the Bit coin market return and volatility. More specifically we document that the residual diversity or freedom of Bit coin network flow scaled by the total system throughput can significantly improve the predictability of Bit coin market return and volatility.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015
Pages1778-1785
Number of pages8
ISBN (Electronic)9781479975600
DOIs
StatePublished - 2015
EventIEEE Symposium Series on Computational Intelligence, SSCI 2015 - Cape Town, South Africa
Duration: 8 Dec 201510 Dec 2015

Publication series

NameProceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015

Conference

ConferenceIEEE Symposium Series on Computational Intelligence, SSCI 2015
Country/TerritorySouth Africa
CityCape Town
Period8/12/1510/12/15

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