A linear programming model for selection of sparse high-dimensional multiperiod portfolios

This paper studies the mean-variance (MV) portfolio problems under static and dynamic settings, particularly for the case in which the number of assets (p) is larger than the number of observations (n). We prove that the classical plug-in estimation seriously distorts the optimal MV portfolio in the...

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Main Authors: Pun, Chi Seng, Wong, Hoi Ying
其他作者: School of Physical and Mathematical Sciences
格式: Article
語言:English
出版: 2018
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在線閱讀:https://hdl.handle.net/10356/87897
http://hdl.handle.net/10220/46617
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