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Bootstrap validation of links of a minimum spanning tree

Author

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  • Musciotto, F.
  • Marotta, L.
  • Miccichè, S.
  • Mantegna, R.N.

Abstract

We describe two different bootstrap methods applied to the detection of a minimum spanning tree obtained from a set of multivariate variables. We show that two different bootstrap procedures provide partly distinct information that can be informative about the investigated complex system. We investigate two case studies by considering daily returns of two portfolios of stocks traded in the US equity markets in different time periods. The first method performs a “row bootstrap” whereas the second method performs a “pair bootstrap” to obtain a bootstrap replica of each correlation coefficient. We show that the parallel use of the two methods can highlight details about the stability of links selected by the minimum spanning tree associated with the correlation matrix of stock portfolios that can be missed by applying only a single bootstrap methods.

Suggested Citation

  • Musciotto, F. & Marotta, L. & Miccichè, S. & Mantegna, R.N., 2018. "Bootstrap validation of links of a minimum spanning tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1032-1043.
    • Handle: RePEc:eee:phsmap:v:512:y:2018:i:c:p:1032-1043
    DOI: 10.1016/j.physa.2018.08.020
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    References listed on IDEAS

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    Cited by:

    1. Celani, Alessandro & Cerchiello, Paola & Pagnottoni, Paolo, 2024. "The topological structure of panel variance decomposition networks," Journal of Financial Stability, Elsevier, vol. 71(C).
    2. Jeremy Turiel & Tomaso Aste, 2019. "Sector Neutral Portfolios: Long memory motifs persistence in market structure dynamics," Papers 1910.08628, arXiv.org, revised Feb 2021.
    3. Tristan Millington & Mahesan Niranjan, 2020. "Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation," Papers 2005.03963, arXiv.org, revised Nov 2020.
    4. Millington, Tristan & Niranjan, Mahesan, 2021. "Construction of minimum spanning trees from financial returns using rank correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).

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