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Hidden interactions in financial markets.

Stavros K Stavroglou1, Athanasios A Pantelous2, H Eugene Stanley3,4

  • 1Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, United Kingdom; stavros.stavroglou@liverpool.ac.uk Athanasios.Pantelous@monash.edu hes@bu.edu.

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|May 16, 2019
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Summary

This study introduces a novel method using symbolic dynamics to uncover hidden causal relationships in financial markets. Findings reveal "dark causality" in sovereign credit default swaps, highlighting complex interdependencies that warrant investor caution.

Keywords:
complex systemsfinancial marketspairs tradingpattern causalitysovereign CDS networks

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Area of Science:

  • Financial markets
  • Causality
  • Symbolic dynamics

Background:

  • Causality is critical for decision-making but often hidden in financial markets.
  • Financial markets exhibit complex interdependencies leading to emergent phenomena like bubbles and crashes.

Purpose of the Study:

  • To develop a method for unveiling the nature of causal interactions in financial markets.
  • To distinguish between positive, negative, and a novel hybrid form of causality termed "dark causality".

Main Methods:

  • Application of symbolic dynamics to probe beneath abstract causality.
  • Development and validation of an algorithm for identifying causal interactions.
  • Testing the method on asset pairs and a network of sovereign credit default swaps (CDS).

Main Results:

  • The proposed method successfully distinguishes between different types of interdependencies.
  • Analysis of sovereign CDS networks reveals a dominance of "dark causality".

Conclusions:

  • "Dark causality" represents a significant, often overlooked, form of interdependency in financial networks.
  • The findings underscore the need for caution when interpreting interdependencies in sovereign CDS markets from an investor's viewpoint.