Causality networks of financial assets

Stavros K. Stavroglou, Athanasios A. Pantelous, Kimmo Soramäki and Konstantin Zuev

Abstract

Through financial network analysis we ascertain the existence of important causal behavior between certain financial assets, as inferred from eight different causality methods. To the best of our knowledge, this is the first extensive comparative analysis of financial networks as produced by various causality methods. In addition, some specific nonlinear causalities are used for the first time in financial network research. 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 have warned us about the financial crisis of 2007–9. 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, thus rendering the comparability and substitutability of these causality methods rather dubious. We also rank the assets in terms of overall out-strength centrality and we find that there is an underlying bonds regime almost monopolizing (in some cases) the causality methods. Finally, using network visualization, we observe an established pattern (ie, across all causalities) of oil’s increasing role as the financial network faced the Chinese stock market crash.