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

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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Bibliographic Details
Main Authors: Pun, Chi Seng, Wong, Hoi Ying
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2018
Subjects:
Investment Analysis
High-dimensional Portfolio Selection
DRNTU::Science::Mathematics
Online Access:https://hdl.handle.net/10356/87897
http://hdl.handle.net/10220/46617
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Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/87897
http://hdl.handle.net/10220/46617

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