Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new interactive model for constructing a tactical global assets allocation through integrating fuzzy scenarios clustering- based approaches (FSCA) with mean-variance (MV) is proposed. This serves as an alternative forecasting rebalance quantitative model to the popular global assets allocation, in which the portfolio is first being observed in contrast with major asset and sub-assets classes which possess upward and downward positive co-movement phenomenon while considering the linkage of cross-market between different time-zones. In addition, fuzzy scenarios clustering would be induced into the MV model so as to adjust the weighting of the risk-return structural matrices. It could further enhance the efficient frontier of a portfolio as well as obtaining opportunity of excess return. By means of global major market indices as the empirical evidences, it shows that the new approach can provide a more efficient frontier for a portfolio and there would be less computational cost to solve MV model.

Original languageEnglish
Title of host publicationSimulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings
PublisherSpringer Verlag
Pages921-928
Number of pages8
ISBN (Print)3540473319, 9783540473312
Publication statusPublished - 2006 Jan 1
Event6th International Conference Simulated Evolution and Learning, SEAL 2006 - Hefei, China
Duration: 2006 Oct 152006 Oct 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4247 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference Simulated Evolution and Learning, SEAL 2006
CountryChina
CityHefei
Period06-10-1506-10-18

Fingerprint

Fuzzy clustering
Clustering
Asset Allocation
Efficient Frontier
Scenarios
Model
Linkage
Weighting
Excess
Forecasting
Computational Cost
Alternatives
Costs
Market

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Wang, H. W. (2006). Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation. In Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings (pp. 921-928). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4247 LNCS). Springer Verlag.
Wang, Hsing Wen. / Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation. Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings. Springer Verlag, 2006. pp. 921-928 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "A new interactive model for constructing a tactical global assets allocation through integrating fuzzy scenarios clustering- based approaches (FSCA) with mean-variance (MV) is proposed. This serves as an alternative forecasting rebalance quantitative model to the popular global assets allocation, in which the portfolio is first being observed in contrast with major asset and sub-assets classes which possess upward and downward positive co-movement phenomenon while considering the linkage of cross-market between different time-zones. In addition, fuzzy scenarios clustering would be induced into the MV model so as to adjust the weighting of the risk-return structural matrices. It could further enhance the efficient frontier of a portfolio as well as obtaining opportunity of excess return. By means of global major market indices as the empirical evidences, it shows that the new approach can provide a more efficient frontier for a portfolio and there would be less computational cost to solve MV model.",
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Wang, HW 2006, Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation. in Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4247 LNCS, Springer Verlag, pp. 921-928, 6th International Conference Simulated Evolution and Learning, SEAL 2006, Hefei, China, 06-10-15.

Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation. / Wang, Hsing Wen.

Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings. Springer Verlag, 2006. p. 921-928 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4247 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Wang HW. Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation. In Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings. Springer Verlag. 2006. p. 921-928. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).