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 language | English |
|---|---|
| Title of host publication | Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings |
| Publisher | Springer Verlag |
| Pages | 921-928 |
| Number of pages | 8 |
| ISBN (Print) | 3540473319, 9783540473312 |
| Publication status | Published - 2006 Jan 1 |
| Event | 6th International Conference Simulated Evolution and Learning, SEAL 2006 - Hefei, China Duration: 2006 Oct 15 → 2006 Oct 18 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4247 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 6th International Conference Simulated Evolution and Learning, SEAL 2006 |
|---|---|
| Country | China |
| City | Hefei |
| Period | 06-10-15 → 06-10-18 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
}
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 proceeding › Conference contribution
TY - GEN
T1 - Fuzzy scenarios clustering-based approach with MV model in optimizing tactical allocation
AU - Wang, Hsing Wen
PY - 2006/1/1
Y1 - 2006/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33751354071&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33751354071&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33751354071
SN - 3540473319
SN - 9783540473312
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 921
EP - 928
BT - Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings
PB - Springer Verlag
ER -