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Int. J. Financial Stud. 2018, 6(2), 52; https://doi.org/10.3390/ijfs6020052

Risk-Based Portfolios with Large Dynamic Covariance Matrices

1
Nomura Asset Management Co., Ltd. 1-12-1 Nihonbashi, Chuo-ku, 103-0027 Tokyo, Japan
2
Graduate School of Business Sciences, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, 112-0012 Tokyo, Japan
3
Department of Risk Engineering, University of Tsukuba, 1-1-1 Tennodai, 305-8577 Tsukuba, Japan
*
Author to whom correspondence should be addressed.
Received: 15 February 2018 / Revised: 9 May 2018 / Accepted: 10 May 2018 / Published: 14 May 2018
(This article belongs to the Special Issue Asset Pricing and Portfolio Choice)
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Abstract

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. View Full-Text
Keywords: (c)DCC-GARCH; nonlinear shrinkage; minimum variance; risk parity; maximum diversification (c)DCC-GARCH; nonlinear shrinkage; minimum variance; risk parity; maximum diversification
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Nakagawa, K.; Imamura, M.; Yoshida, K. Risk-Based Portfolios with Large Dynamic Covariance Matrices. Int. J. Financial Stud. 2018, 6, 52.

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