DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Woo Chang | - |
dc.contributor.advisor | 김우창 | - |
dc.contributor.author | Jang, Ju Ri | - |
dc.contributor.author | 장주리 | - |
dc.date.accessioned | 2017-03-29T02:33:20Z | - |
dc.date.available | 2017-03-29T02:33:20Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=663367&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/221450 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 산업및시스템공학과, 2016.8 ,[iv, 32 p. :] | - |
dc.description.abstract | For portfolio management in the real-world, it is required that a portfolio has a manageable number of assets and stable performance. However, much research has pointed out that the Markowitz model, which is a classical model in portfolio theory, forms a portfolio with many different assets that may have unstable performance. Therefore, in this paper, we focus on developing a portfolio selection model which constructs a sparse and robust optimal portfolio. In order to achieve our research goal, we introduce two kinds of optimization problems. The first one is a $L_2$ -norm regularized cardinality constraint portfolio and the second one is cardinality constrained robust optimization portfolio with ellipsoidal uncertainty set. Moreover, we formulate a convex optimization problem for these proposed models using semi-definite relaxation. The outcomes of our empirical tests show that portfolios obtained by our model have smaller cardinalities and better out-of-sample performances than those of cardinality constrained Markowitz optimal portfolios. A large part of financial business is now being automated. Our portfolios give the investors new opportunity to obtain the desired properties | - |
dc.description.abstract | sparsity and robustness. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Portfolio selection | - |
dc.subject | Sparse portfolio | - |
dc.subject | Robust optimization | - |
dc.subject | Semi-definite relaxation | - |
dc.subject | 자산선택 | - |
dc.subject | 희소 포트폴리오 | - |
dc.subject | 로버스트 최적화 | - |
dc.subject | 놈 정규화 | - |
dc.subject | 반 확정 완화 기법 | - |
dc.title | Sparse and robust portfolio selection via semi-definite relaxation | - |
dc.title.alternative | 반 확정 완화 기법을 통한 희소-강건 포트폴리오 최적화 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :산업및시스템공학과, | - |
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