Anticipating Abrupt Changes in Complex Networks: Significant Falls in the Price of a Stock Index

  • Antonio CordobaEmail author
  • Christian Castillejo
  • Juan J. García-Machado
  • Ana M. Lara
Part of the Understanding Complex Systems book series (UCS)


Early prediction of abrupt changes in complex systems is of great interest in preventing unwanted effects. This has recently led to the establishment of indicators whose evolution may be indicative of some of such changes. Here we present a criterion to predict the sharp fall in the prices of a stock market index. We have studied the moving networks constituted by the companies included in several indexes (IBEX35, CAC40, DAX30 and Euro Stoxx50), constructing the corresponding “Minimal Spanning Tree (MST)”. When the number of leading nodes in the network decreases in a substantial manner, the network has few leaders, and if those suffer any fall, the index might fall as well. By means of this hypothesis, we are looking for a rotation direction beforehand, a downward rotation. Using daily closing price series from 2007 to 2017 for these indexes, we can point out that when the number of leading nodes is small, and the average correlation of companies forming an index decreases, placing itself below 0.4–0.5, depending on the index, and this decrease is accompanied by a significant increase in the correlation deviation, the price tends to fall at around 70% of reliability.


Complex networks Phase transitions Stock markets Price predictability Financial analysis Econophysics 



AC acknowledges Junta de Andalucía (Spain) by partially funding to his research group (FQM-122).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Antonio Cordoba
    • 1
    Email author
  • Christian Castillejo
    • 2
  • Juan J. García-Machado
    • 3
  • Ana M. Lara
    • 2
  1. 1.Departamento de Física de la Materia CondensadaUniversidad de SevillaSevillaSpain
  2. 2.Instituto IBTParque Empresarial Nuevo TorneoSevillaSpain
  3. 3.Departamento de Economía FinancieraContabilidad y Dirección de Operaciones, Universidad de HuelvaHuelvaSpain

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