Hidden Interactions in Financial Markets
Proceedings of the National Academy of Sciences (PNAS) of the United States of America, Volume x, Issue x, p. 1-6, May 2019, DOI: 10.1073/pnas.1819449116
Posted: 28 Jan 2018 Last revised: 16 May 2019
Date Written: May 13, 2019
The hidden nature of causality is a puzzling, yet critical notion for effective decision-making. Financial markets are characterized by fluctuating interdependencies which seldom give rise to emergent phenomena such as bubbles or crashes. In this paper, we propose a method based on symbolic dynamics, which probes beneath the surface of abstract causality and unveils the nature of causal interactions. Our method allows distinction between positive and negative interdependencies as well as a hybrid form that we refer to as “dark causality.” We propose an algorithm which is validated by models of a priori defined causal interaction. Then, we test our method on asset pairs and on a network of sovereign credit default swaps (CDS). Our findings suggest that dark causality dominates the sovereign CDS network, indicating interdependencies which require caution from an investor’s perspective.
Keywords: financial markets; pattern causality; complex systems; sovereign CDS networks; pairs trading
JEL Classification: C00, C01, C02, C10
Suggested Citation: Suggested Citation