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学术报告:A portfolio rebalancing problem: sparsity versus robustness
发表时间:2019-03-12 阅读次数:247次

时间:2019313日下午2

地点:管理学院506会议室

主讲:Zhihua Zhao

 

摘要:Institutional investors rebalance their portfolios regularly to control the risk profile of their holdings. We propose a new portfolio rebalancing method with embedded sparsity and robustness, two highly demanded properties by portfolio managers. Sparsity, quantified by the l0 norm, has the desirable property to trade only a small number of assets in the portfolio and hence potentially reduce trading cost and improve out-of-sample performance. Robustness, achieved by the ellipsoidal uncertainty set for asset returns, has the important property of mitigating estimation errors. Assuming diagonal covariance matrices, we derive a closed-form solution to our problem. This analytical solution allows us to identify two key factors in portfolio rebalancing, namely, the consistent convergence of optimal portfolio positions and the movement of the trading critical points. For non-diagonal covariance matrices, we propose an efficient Alternating Direction Method of Multipliers, where each subproblem admits a closed-form solution. To develop further intuition and insights, we illustrate these findings via simulated data sets and conduct out-of-sample performance analysis of the proposed method on actual data from the Chinese stock market

Key words:Portfolio rebalancing, sparsity and robustness, trade-off analysis, parameter uncertainty Joint work with Fengmin Xu and Donglei Du.

 

报告人简介:Dr. Zhihua Zhao, currently serving as a PhD student in the School of Economics and Finance, Xi’an Jiaotong University. His main research interests are quantitative finance, statistics, sparse optimization theory and algorithms involved in big data and microscopic research on typical financial issues. His publications have appeared in famous journals, including Neural Computing & Applications, Science China Mathematics, and Journal of the Operational Research Society etc. His research has been recognized by numerous awards and supported by two National Natural Science  oundation of China as well as a Key Program of the NSF. He has been a visiting scholar in Academy of Mathematics and Systems Science, Chinese Academy of Sciences, and Xidian University ect.

 

 

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