Network Causality Structures among Bitcoin and other Financial Assets: A Directed Acyclic Graph Approach

Qiang Ji, Elie Bouri (), Rangan Gupta and David Roubaud ()

No 201729, Working Papers from University of Pretoria, Department of Economics

Abstract: Unlike prior studies that have mostly relied on ad hoc network structures, we use a data-driven methodology, namely the directed acyclic graph (DAG), to uncover the contemporaneous and lagged causal relations among Bitcoin and a set of financial assets. The DAG methodology allows the identification of networks of causality based on the observed correlations and partial correlations approach, without making a priori causal assumptions. The main results indicate that the Bitcoin market is quite isolated, especially during its bull market state. We also conduct forecast error variance decompositions and show that the influence of different financial assets on Bitcoin up to the 20-day horizon does not account for more than 10% of innovations in all cases.

Keywords: Bitcoin; financial assets; integration; causality; directed acyclic graph (search for similar items in EconPapers)
JEL-codes: G11 G15 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2017-04
New Economics Papers: this item is included in nep-pay
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Citations: View citations in EconPapers (10)

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Journal Article: Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach (2018)
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