Mesoscopic structure of the stock market and portfolio optimization

Sebastiano Michele Zema (), Giorgio Fagiolo, Tiziano Squartini and Diego Garlaschelli
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Sebastiano Michele Zema: Scuola Normale Superiore
Giorgio Fagiolo: Scuola Superiore Sant’Anna
Tiziano Squartini: IMT Institute for Advanced Studies
Diego Garlaschelli: IMT Institute for Advanced Studies

Journal of Economic Interaction and Coordination, 2025, vol. 20, issue 2, No 1, 307-333

Abstract: 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.

Keywords: Random matrix theory; Community detection; Mesoscopic structures; Portfolio optimization (search for similar items in EconPapers)
JEL-codes: C02 D85 G11 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11403-024-00426-y

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