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Concentration, Information, and Distributional Stability in High-Dimensional Portfolios: A Talagrand Stability Index
Irina Georgescu1, Jani Kinnunen2
1Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Calea Dorobanți, 15-17, Sector 1, 010552 Bucharest, Romania.
Entropy (Basel, Switzerland)
|July 28, 2026
Summary
High-dimensional financial portfolios become more stable with increased size, showing reduced risk and better diversification. However, heavy-tailed returns decrease stability compared to Gaussian returns.
Area of Science:
- Quantitative Finance
- Financial Risk Management
- Network Science
Background:
- High-dimensional financial portfolios present unique risk management challenges.
- Understanding portfolio stability is crucial for robust investment strategies.
Purpose of the Study:
- To investigate the stability of high-dimensional financial portfolios.
- To introduce a novel measure for distributional robustness in portfolio analysis.
Main Methods:
- Utilized concentration inequalities, information-theoretic measures, and optimal transport metrics.
- Employed financial network analysis and introduced the Talagrand Stability Index (TSI).
- Evaluated multivariate Gaussian and Student-t return distributions for Equal Weight and Regularized Minimum Variance portfolios.
Main Results:
- Increasing portfolio dimension enhances stability, reduces risk, and improves diversification.
- The Talagrand Stability Index (TSI) decreases with portfolio dimension.
- Heavy-tailed distributions (Student-t) exhibit lower stability and stronger dependence than Gaussian distributions.
Conclusions:
- High-dimensional portfolios demonstrate increased concentration and stability.
- The proposed Talagrand Stability Index (TSI) offers a robust measure of portfolio distributional stability.
- Empirical results suggest modest stability advantages for Regularized Minimum Variance portfolios, dependent on specific outcomes.
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