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Multilayer Aggregation with Statistical Validation: Application to Investor Networks.

Kęstutis Baltakys1, Juho Kanniainen2, Frank Emmert-Streib3,4

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This summary is machine-generated.

This study introduces a new method for analyzing multilayer investor networks, enhancing data integration and validation. The findings reveal that capital-based households exhibit high centrality, suggesting they are well-informed investors.

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Area of Science:

  • Network Science
  • Financial Economics
  • Data Analysis

Background:

  • Multilayer networks are increasingly significant across various scientific domains, including finance.
  • Analyzing investor networks requires robust methods for integrating diverse data types and ensuring statistical validity.

Purpose of the Study:

  • To develop a tractable procedure for multilayer network aggregation with statistical validation.
  • To introduce transaction bootstrapping and investor categorization for improved network analysis.
  • To apply these methods to Finnish shareholder data for insights into investor behavior.

Main Methods:

  • A novel multilayer aggregation procedure based on statistical validation.
  • Transaction bootstrapping for enhanced statistical validation in network inference.
  • Investor categorization to maintain network size and increase node observations.

Main Results:

  • The aggregation procedure effectively integrates security-wise and time-wise information in investor networks.
  • Transaction bootstrapping improves the statistical reliability of inferred network relationships.
  • Investor categorization aids inference, particularly for less liquid securities.
  • Window size significantly impacts the number of inferred relationships.
  • Finnish capital-based households demonstrate high centrality in investor networks.

Conclusions:

  • The developed procedure offers a versatile tool for multilayer network analysis beyond finance, applicable to gene, transportation, and social networks.
  • High centrality of capital-based households suggests their role as well-informed investors within information channels.
  • The study provides a statistically validated framework for understanding complex investor networks.