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Applied Stochastic Models in Business and Industry
Article . 2019 . Peer-reviewed
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Article . 2020
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Vector error correction models to measure connectedness of Bitcoin exchange markets

Vector error correction models to measure connectedness of bitcoin exchange markets
Authors: Giudici, Paolo; Pagnottoni, Paolo;

Vector error correction models to measure connectedness of Bitcoin exchange markets

Abstract

AbstractBitcoins are traded on various exchange platforms and, therefore, prices may differ across trading venues. We aim to investigate return connectedness across eight of the major exchanges of Bitcoin, both from a static and a dynamic viewpoint. To this end, we employ an extension of the order‐invariant forecast error variance decomposition proposed by Diebold and Yilmaz (2012) to a generalized vector error correction framework. Our results suggest that there is strong connectedness among the exchanges, as expected, although some of them behave dissimilarly. We identify Bitfinex and Coinbase as leading exchanges during the considered period, while Kraken as a follower exchange. We also obtain that connectedness across exchanges is strongly dynamic, as it evolves over time.

Country
Italy
Keywords

market linkage, spillover, 330, Statistics, bitcoin, forecast error variance decomposition, market linkages, market risk, Bitcoin; forecast error variance decomposition; market linkages; market risk; spillovers; vector autoregression; vector error correction, vector autoregression, vector error correction, spillovers, Bitcoin

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 1%
Top 10%
Top 1%
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