When “time varying” volatility meets “transaction cost” in portfolio selection
We propose a new strategy for mean–variance portfolio selection that tackles transaction costs and change detection in covariance matrix simultaneously. The new strategy solely rebalances the portfolio when change points are detected in the covariance matrix, striking an optimal trade-off between re...
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Published in | Journal of empirical finance Vol. 73; pp. 220 - 237 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.09.2023
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Abstract | We propose a new strategy for mean–variance portfolio selection that tackles transaction costs and change detection in covariance matrix simultaneously. The new strategy solely rebalances the portfolio when change points are detected in the covariance matrix, striking an optimal trade-off between rebalancing the portfolio to capturing the recent information in return data and avoiding excessive trading. Our empirical results suggest favorable out-of-sample performance of the new strategy in terms of portfolio variance, portfolio turnovers and portfolio sharpe ratio with transaction cost. We also show that these gains come from the improved accuracy for covariance matrix prediction and the ability for tracking significant changes in covariance matrix.
•A new method is proposed for mean-variance portfolio selection.•It mainly tackles the transaction cost reduction and change detection in covariance matrix.•The new method achieves out-of-sample performance improvement. |
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AbstractList | We propose a new strategy for mean–variance portfolio selection that tackles transaction costs and change detection in covariance matrix simultaneously. The new strategy solely rebalances the portfolio when change points are detected in the covariance matrix, striking an optimal trade-off between rebalancing the portfolio to capturing the recent information in return data and avoiding excessive trading. Our empirical results suggest favorable out-of-sample performance of the new strategy in terms of portfolio variance, portfolio turnovers and portfolio sharpe ratio with transaction cost. We also show that these gains come from the improved accuracy for covariance matrix prediction and the ability for tracking significant changes in covariance matrix.
•A new method is proposed for mean-variance portfolio selection.•It mainly tackles the transaction cost reduction and change detection in covariance matrix.•The new method achieves out-of-sample performance improvement. |
Author | Gibberd, A. Liao, Y. Bu, D. Wen, T. Qiao, W. Li, E. |
Author_xml | – sequence: 1 givenname: W. surname: Qiao fullname: Qiao, W. email: qiaowen1982@163.com organization: School of Economics and Management, Ningbo University of Technology, China – sequence: 2 givenname: D. surname: Bu fullname: Bu, D. email: di.bu@mq.edu.au organization: Department of Applied Finance, Macquarie University, Australia – sequence: 3 givenname: A. surname: Gibberd fullname: Gibberd, A. email: a.gibberd@lancaster.ac.uk organization: Department of Mathematics & Statistics, Lancaster University, UK – sequence: 4 givenname: Y. surname: Liao fullname: Liao, Y. email: yin.liao@mq.edu.au organization: Department of Applied Finance, Macquarie University, Australia – sequence: 5 givenname: T. surname: Wen fullname: Wen, T. email: tingwen1225@163.com organization: Chongqing Research Center of High-skilled Personnel Development, China – sequence: 6 givenname: E. surname: Li fullname: Li, E. email: ethanli.syd@gmail.com organization: Sydney Boys High School, Australia |
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Cites_doi | 10.1080/10618600.2017.1302340 10.2307/2331042 10.1287/opre.2017.1699 10.1093/rfs/hhm075 10.1016/j.jeconom.2018.11.007 10.1093/rfs/12.5.937 10.1017/S0022109010000335 10.1080/01621459.1984.10477105 10.1017/S0022109015000526 10.1111/j.1467-9868.2005.00490.x 10.1093/rfs/hhx052 10.1016/j.jbankfin.2012.05.005 10.1016/S0927-5398(03)00007-0 10.3905/jpm.2007.690606 10.1111/1540-6261.00580 10.3905/jpm.2015.41.3.097 10.1016/S0304-405X(02)00259-3 10.2307/2171927 10.1080/01621459.1994.10476870 10.3905/jpm.2012.38.2.014 10.1111/jofi.12513 10.1111/jofi.12080 10.1561/2200000016 10.1016/j.jeconom.2019.04.028 10.1080/07350015.2017.1345683 10.1017/S0022109012000117 10.1111/j.2517-6161.1996.tb02080.x 10.1214/12-BA729 10.1287/mnsc.1080.0986 10.1093/biostatistics/kxm045 10.1016/j.jet.2016.06.001 10.1111/0022-1082.00327 10.1093/rfs/hhy105 |
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Keywords | Large scale portfolio Transaction cost C13 G11 Sparse time variation Covariance matrix C51 Structural change C61 |
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Stud. doi: 10.1093/rfs/hhy105 contributor: fullname: Ao |
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Snippet | We propose a new strategy for mean–variance portfolio selection that tackles transaction costs and change detection in covariance matrix simultaneously. The... |
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SubjectTerms | Covariance matrix Large scale portfolio Sparse time variation Structural change Transaction cost |
Title | When “time varying” volatility meets “transaction cost” in portfolio selection |
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