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Updated: Sep 26, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Smart network based portfolios.

Gian Paolo Clemente1, Rosanna Grassi2, Asmerilda Hitaj3

  • 1Dipartimento di Discipline Matematiche, Finanza Matematica ed Econometria, Università Cattolica del Sacro Cuore, Milan, Italy.

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Network theory enhances portfolio allocation strategies. Network-based portfolios show improved performance and reduced risk compared to standard methods in out-of-sample tests.

Keywords:
DependenceInterconnectednessMean-varianceNetworksPortfolio optimizationSmart Beta strategies

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Area of Science:

  • Quantitative Finance
  • Network Theory
  • Computational Finance

Background:

  • Portfolio allocation is crucial for managing investment risk.
  • Traditional methods often rely on correlation matrix estimation.
  • Network theory offers novel approaches to financial modeling.

Purpose of the Study:

  • To enhance portfolio allocation using network theory.
  • To integrate correlation network structures into risk-based models.
  • To compare standard and network-based portfolio optimization approaches.

Main Methods:

  • Formulating and solving portfolio allocation problems using standard and network-based approaches.
  • Utilizing correlation network dependence structures.
  • Employing sample, shrinkage, and depth-based covariance matrix estimators.
  • Implementing strategies on high-dimensional portfolios.

Main Results:

  • Network-based portfolios consistently outperform standard portfolios.
  • Lower risk is observed in network-based portfolios.
  • Performance was evaluated using out-of-sample testing.

Conclusions:

  • Network theory provides a robust framework for portfolio optimization.
  • Network-based strategies offer superior risk-adjusted returns.
  • The findings suggest practical applications in financial risk management.