Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

The Application of Robust Statistics to Stock Portfolio Problem

Authors
Xiongying Li, Jiahao Hong, Binhui Wang
Corresponding Author
Xiongying Li
Available Online April 2015.
DOI
https://doi.org/10.2991/icmra-15.2015.247How to use a DOI?
Keywords
portfolio; outlier; Fast-MCD; robust regression
Abstract
Portfolio theory is used to measure the expected return and risk on the basis of the history data of security return ratio,but in fact there is always excessively high or low return ratio caused by some short-term fundamental good or bad news in the history data of return ratio.We introduce the robust statistic idea into the portfolio theory in this paper,thus reduce outliers’ influence on portfolio decision in the history data of return ratios,bring back the portfolio on its long-term investment value track.For the classic Markowits mean-variance model and Sharp’s single index model, we focused on the robust estimate method Fast-MCD and robust regression method,and apply them to solution processing in the portfolio model and obtained good results .
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Proceedings
3rd International Conference on Mechatronics, Robotics and Automation
Part of series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.247How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Xiongying Li
AU  - Jiahao Hong
AU  - Binhui Wang
PY  - 2015/04
DA  - 2015/04
TI  - The Application of Robust Statistics to Stock Portfolio Problem
BT  - 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 1285
EP  - 1289
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.247
DO  - https://doi.org/10.2991/icmra-15.2015.247
ID  - Li2015/04
ER  -