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Mesoscopic structure of the stock market and portfolio optimization

Author

Listed:
  • Sebastiano Michele Zema

    (Scuola Normale Superiore
    Scuola Superiore Sant’Anna)

  • Giorgio Fagiolo

    (Scuola Superiore Sant’Anna)

  • Tiziano Squartini

    (IMT Institute for Advanced Studies)

  • Diego Garlaschelli

    (IMT Institute for Advanced Studies
    University of Leiden)

Abstract

The idiosyncratic and systemic components of market structure have been shown to be responsible for the departure of the optimal mean-variance allocation from the heuristic ‘equally weighted’ portfolio. In this paper, we exploit clustering techniques derived from Random Matrix Theory to study a third, intermediate (mesoscopic) market structure that turns out to be the most stable over time and provides important practical insights from a portfolio management perspective. First, we illustrate the benefits, in terms of predicted and realized risk profiles, of constructing portfolios by filtering out both random and systemic co-movements from the correlation matrix. Second, we redefine the portfolio optimization problem in terms of stock clusters that emerge after filtering. Finally, we propose a new wealth allocation scheme that attaches equal importance to stocks belonging to the same community and show that it further increases the reliability of the constructed portfolios. Results are robust across different time spans, cross sectional dimensions and set of constraints defining the optimization problem.

Suggested Citation

  • Sebastiano Michele Zema & Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2025. "Mesoscopic structure of the stock market and portfolio optimization," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 20(2), pages 307-333, April.
  • Handle: RePEc:spr:jeicoo:v:20:y:2025:i:2:d:10.1007_s11403-024-00426-y
    DOI: 10.1007/s11403-024-00426-y
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    More about this item

    Keywords

    Random matrix theory; Community detection; Mesoscopic structures; Portfolio optimization;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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