A behavioral approach to instability pathways in financial markets

Nicolo' Pecora, Alessandro Spelta, Andrea Flori, Sergey Buldyrev, Fabio Pammolli

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

We introduce an indicator that aims to detect the emergence of market instabilities by quantifying the intensity of self-organizing processes arising from stock returns’ co-movements. In financial markets, phenomena like imitation, herding and positive feedbacks characterize the emergence of endogenous instabilities, which can modify the qualitative and quantitative behavior of the underlying system. The impossibility to formalize ex-ante the dynamic laws that rule the evolution of financial systems motivates the use of a parsimonious synthetic indicator to detect the disruption of an existing equilibrium configuration. Here we show that the emergence of an interconnected sub-graph of stock returns co-movements from a broader market index is a signal of an out-of-equilibrium transition of the underlying system. To test the validity of our approach, we propose a model-free application that builds on the identification of up and down market phases.
Original languageEnglish
Pages (from-to)N/A-N/A
JournalNature Communications
DOIs
Publication statusPublished - 2020

Keywords

  • Complex systems
  • Financial Instability
  • Investment strategies
  • Leading Temporal Module

Fingerprint

Dive into the research topics of 'A behavioral approach to instability pathways in financial markets'. Together they form a unique fingerprint.

Cite this