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Statistical estimation of time-varying complexity in financial networks

  • Aditi Rai
  • Avijit Bansal
  • Anindya S. ChakrabartiEmail author
Regular Article
  • 18 Downloads

Abstract

In this paper, we propose a method to characterize the relation between financial market instability and the underlying complexity by identifying structural relationships in dynamics of stock returns. The proposed framework is amenable to statistical and econometric estimation techniques, and at the same time, provides a theoretical link between stability of a financial system and the embedded heterogeneity, in line of the May-Wigner result. We estimate the interaction matrix of stock returns through a vector autoregressive structure and compute heterogeneity in the strength of connections for time periods covering periods before the 2007–08 crisis, during the crisis and post-crisis recovery. We show that the empirically estimated heterogeneity increased substantially during time of financial crisis and subsequently tapered off, demonstrating concurrent rise and fall in the degree of instability.

Graphical abstract

Keywords

Statistical and Nonlinear Physics 

Supplementary material

10051_2019_10161_MOESM1_ESM.pdf (152 kb)
Statistical estimation of time-varying complexity in financial networks

References

  1. 1.
    N. Arinaminpathy, S. Kapadia, R.M. May, Proc. Natl. Acad. Sci. 2012, 201213767 (2012) Google Scholar
  2. 2.
    G. Cimini, M. Serri, PLoS One 11, e0161642 (2016) CrossRefGoogle Scholar
  3. 3.
    A.G. Haldane, R.M. May, Nature 469, 351 (2011) ADSCrossRefGoogle Scholar
  4. 4.
    D. Helbing, Nature 497, 51 (2013) ADSCrossRefGoogle Scholar
  5. 5.
    X. Huang, I. Vodenska, S. Havlin, H.E. Stanley, Sci. Rep. 3, 1219 (2013) ADSCrossRefGoogle Scholar
  6. 6.
    S. Thurner, S. Poledna, Sci. Rep. 3, 1888 (2013) ADSCrossRefGoogle Scholar
  7. 7.
    N. Beale, D.G. Rand, H. Battey, K. Croxson, R.M. May, M.A. Nowak, Proc. Natl. Acad. Sci. 108, 12647 (2011) ADSCrossRefGoogle Scholar
  8. 8.
    N. Johnson, T. Lux, Nature 469, 302 (2011) ADSCrossRefGoogle Scholar
  9. 9.
    R.M. May, Nature 238, 413 (1972) ADSCrossRefGoogle Scholar
  10. 10.
    S. Sinha, Sci. Culture (Special Issue on Econophysics) 72, 454 (2010) Google Scholar
  11. 11.
    R.H. Heiberger, Physica A 393, 376 (2014) ADSCrossRefGoogle Scholar
  12. 12.
    S. Markose, S. Giansante, A.R. Shaghaghi, J. Econ. Behav. Organ. 83, 627 (2012) CrossRefGoogle Scholar
  13. 13.
    D. Petrone, V. Latora, Sci. Rep. 8, 5561 (2018) ADSCrossRefGoogle Scholar
  14. 14.
    H.M. Hastings, J. Theor. Biol. 97, 155 (1982) CrossRefGoogle Scholar
  15. 15.
    R. Gibrat, Les Inegalites Economiques (Sirey, Paris, 1933) Google Scholar
  16. 16.
    H. Lütkepohl, New introduction to multiple time series analysis (Springer Science & Business Media, 2005) Google Scholar
  17. 17.
    W.A. Fuller, Introduction to Statistical Time Series (John Wiley, New York, 1976) Google Scholar
  18. 18.
    R.K. Pan, S. Sinha, Phys. Rev. E 76, 046116 (2007) ADSCrossRefGoogle Scholar
  19. 19.
    J.E. Cohen, C.M. Newman, Ann. Probab. 1984, 283 (1984) CrossRefGoogle Scholar
  20. 20.
    P. Kirk, D.M.Y. Rolando, A.L. MacLean, M.P.H. Stumpf, New J. Phys. 17, 083025 (2015) ADSMathSciNetCrossRefGoogle Scholar
  21. 21.
    S. Gualdi, G. Cimini, K. Primicerio, R.D. Clemente, D. Challet, Sci. Rep. 6, 39467 (2016) ADSCrossRefGoogle Scholar
  22. 22.
    S. Sinha, S. Sinha, Phys. Rev. E 71, 020902 (2005) ADSCrossRefGoogle Scholar
  23. 23.
    S. Sinha, Physica A 346, 147 (2005) ADSCrossRefGoogle Scholar
  24. 24.
    H.K. Pharasi, K. Sharma, R. Chatterjee, A. Chakraborti, F. Leyvraz, T.H. Seligman, New J. Phys. 20, 103041 (2018) ADSCrossRefGoogle Scholar

Copyright information

© EDP Sciences / Società Italiana di Fisica / Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Aditi Rai
    • 1
  • Avijit Bansal
    • 2
  • Anindya S. Chakrabarti
    • 3
    Email author
  1. 1.Indian Institute of Management, VastrapurAhmedabadIndia
  2. 2.Finance & Accounting Area, Indian Institute of Management, VastrapurAhmedabadIndia
  3. 3.Economics Area, Indian Institute of Management, VastrapurAhmedabadIndia

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