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Risk-Based Portfolios with Large Dynamic Covariance Matrices
http://hdl.handle.net/2241/00153566
http://hdl.handle.net/2241/001535665799b4c0-e4c4-4262-92a5-08a7cb9653a7
名前 / ファイル | ライセンス | アクション |
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IJFS_6-2-52 (291.0 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2018-10-16 | |||||
タイトル | ||||||
タイトル | Risk-Based Portfolios with Large Dynamic Covariance Matrices | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Nakagawa, Kei
× Nakagawa, Kei× Imamura, Mitsuyoshi× Yoshida, Kenichi |
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著者別名 |
吉田, 健一
× 吉田, 健一 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In the field of portfolio management, practitioners are focusing increasingly on risk-based portfolios rather than on mean-variance portfolios. Risk-based portfolios are constructed based solely on covariance matrices, and include methods such as minimum variance (MV), risk parity (RP), and maximum diversification (MD). It is well known that the performance of a mean-variance portfolio depends on the accuracy of the estimations of the inputs. However, no studies have examined the relationship between the performance of risk-based portfolios and the estimated accuracy of covariance matrices. In this research, we compare the performance of risk-based portfolios for several estimation methods of covariance matrices in the Japanese stock market. In addition, we propose a highly accurate estimation method called cDCC-NLS, which incorporates nonlinear shrinkage into the cDCC-GARCH model. The results confirm that (1) the cDCC-NLS method shows the best estimation accuracy, (2) the RP and MD do not depend on the estimation accuracy of the covariance matrix, and (3) the MV does depend on the estimation accuracy of the covariance matrix. | |||||
書誌情報 |
International Journal of Financial Studies 巻 6, 号 2, p. 52, 発行日 2018-05 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 2227-7072 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.3390/ijfs6020052 | |||||
権利 | ||||||
権利情報 | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | |||||
著者版フラグ | ||||||
値 | publisher | |||||
出版者 | ||||||
出版者 | MDPI |