完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Ong, CS | en_US |
dc.contributor.author | Huang, HJ | en_US |
dc.contributor.author | Tzeng, GH | en_US |
dc.date.accessioned | 2014-12-08T15:18:12Z | - |
dc.date.available | 2014-12-08T15:18:12Z | - |
dc.date.issued | 2005-10-15 | en_US |
dc.identifier.issn | 0096-3003 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1016/j.amc.2004.10.080 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/13164 | - |
dc.description.abstract | As we know, the performance of the mean-variance approach depends on the accurate forecast of the return rate. However, the conventional method (e.g. arithmetic mean or regression-based method) usually cannot obtain a satisfied solution especially under the small sample situation. In this paper, the proposed method which incorporates the grey and possibilistic regression models formulates the novel portfolio selection model. In order to solve the multi-objective quadric programming problem, multi-objective evolution algorithms (MOEA) is employed. A numerical example is also illustrated to show the procedures of the proposed method. On the basis of the numerical results, we can conclude that the proposed method can provide the more flexible and accurate results. (c) 2004 Elsevier Inc. All rights reserved. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | mean-variance approach | en_US |
dc.subject | portfolio selection | en_US |
dc.subject | Grey model | en_US |
dc.subject | possibilistic regression model | en_US |
dc.subject | multi-objective evolution algorithms (MOEA) | en_US |
dc.title | A novel hybrid model for portfolio selection | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1016/j.amc.2004.10.080 | en_US |
dc.identifier.journal | APPLIED MATHEMATICS AND COMPUTATION | en_US |
dc.citation.volume | 169 | en_US |
dc.citation.issue | 2 | en_US |
dc.citation.spage | 1195 | en_US |
dc.citation.epage | 1210 | en_US |
dc.contributor.department | 科技管理研究所 | zh_TW |
dc.contributor.department | Institute of Management of Technology | en_US |
dc.identifier.wosnumber | WOS:000232811600037 | - |
dc.citation.woscount | 19 | - |
顯示於類別: | 期刊論文 |