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Causality Networks of Financial Assets

Journal of Network Theory in Finance, Volume 3, Issue 2, pp 17-67, June 2017, DOI: 10.21314/JNTF.2017.029

73 Pages Posted: 22 Dec 2016 Last revised: 20 Jul 2017

Stavros Stavroglou

Department of Mathematical Sciences and Institute for Risk and Uncertainty, University of Liverpool, UK

Athanasios A. Pantelous

University of Liverpool, Department of Mathematical Sciences and Institute for Risk and Uncertainty

Kimmo Soramaki

Financial Network Analytics Ltd

Konstantin Zuev

California Institute of Technology

Date Written: December 22, 2016

Abstract

Through financial network analysis we ascertain the existence of important causal behavior among certain financial assets, as inferred by eight different causality methods. Our results contradict the Efficient Market Hypothesis and open new horizons for further investigation and possible arbitrage opportunities. Moreover, we find some evidence that two of the causality methods used, at least to some extent, could warn us about the financial crisis of 2007-2009. Furthermore, we test the similarity percentage of the eight causality methods and we find that the most similar pair of causality-induced networks is on average less than 50% similar throughout the time period examined, rendering thus the comparability and substitutability among those causality methods rather dubious. We also rank both the causal relationships and the assets in terms of overall causality exertion and we find that there is an underlying bonds regime almost monopolising in some cases the realm of causality. Finally, we observe a recurring pattern of Oil's rising role as the financial network faces the Chinese stock market crash.

Keywords: Causality, Efficient Market Hypothesis, Network Theory, Bonds, Oil

JEL Classification: C01; G14; G10; L14

Suggested Citation

Stavroglou, Stavros and Pantelous, Athanasios A. and Soramaki, Kimmo and Zuev, Konstantin, Causality Networks of Financial Assets (December 22, 2016). Journal of Network Theory in Finance, Volume 3, Issue 2, pp 17-67, June 2017, DOI: 10.21314/JNTF.2017.029. Available at SSRN: https://ssrn.com/abstract=2888783 or http://dx.doi.org/10.2139/ssrn.2888783

Stavros Stavroglou

Department of Mathematical Sciences and Institute for Risk and Uncertainty, University of Liverpool, UK ( email )

Liverpool, L69 7ZA
United Kingdom

Athanasios A. Pantelous (Contact Author)

University of Liverpool, Department of Mathematical Sciences and Institute for Risk and Uncertainty ( email )

Liverpool, L69 7ZA
United Kingdom

Kimmo Soramaki

Financial Network Analytics Ltd ( email )

Spain

Konstantin Zuev

California Institute of Technology ( email )

Pasadena, CA 91125
United States

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