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A Study on Assets Categorizations and Optimal Allocation via an Improved Algorithm

  • Guang Liu
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

The efficiency of assets allocation is essential to investment performance. To deal with the dynamic optimization of industry asset allocation, an improved algorithm (the Index Hierarchical Structure Algorithm, IHSA) is applied to 20 industry indexes according to different sample period, and proved to deduce stabilized industry categorizations. Then, a series of different size industry portfolios are constructed by the algorithm, and their monthly rate of returns are compared with 369 open-ended funds (including 263 growth funds and 106 index funds). The results indicate that the performance of each industry portfolio is better than most of the sample funds in the early sample period, especially than index funds. The algorithm provides a useful guidance for industry allocation and active asset management.

Keywords

Index hierarchical structure algorithm Industry categorization Asset allocation Topological space 

Notes

Acknowledgments

This work is financially supported by the Guangdong Province-sponsored Philosophy and Social Science Funding Program (GD14XYJ16) and the Guangdong Province Education Department—sponsored Platform Funding Program for Humanities and Social Sciences (2014WQNCX074).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Guang Liu
    • 1
  1. 1.Guangzhou UniversityGuangzhouChina

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