Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)

An Empirical Analysis of W&R Based on Listed Companies' Investments in Vocational Education

Authors
Yao Huang, Hai-ping Huang
Corresponding Author
Yao Huang
Available Online July 2017.
DOI
10.2991/iccse-17.2017.45How to use a DOI?
Keywords
Vocational education, W&R, Empirical analysis
Abstract

W&R, an expert system of securities trading software, is tested through statistical and empirical analyses based on true data about vocational education on securities that are publicly available. With annual net profit margin, rate of return and win as management objectives. The non-directional W&R indicators are empirically analyzed based on theories of mathematical statistics. At last, annual rate of return and net profit margin of the W&R are determined to be 61.62 and 61.63% of Shanghai Stock Exchange indexes. Investment solutions with a win rate of 59.72% and an annual rate of return that is 6.6 times as high as annual interest rate of bank deposits are optional for those investors who are crazy about seeking high profits and willing to undertake risks.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
Series
Advances in Computer Science Research
Publication Date
July 2017
ISBN
10.2991/iccse-17.2017.45
ISSN
2352-538X
DOI
10.2991/iccse-17.2017.45How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yao Huang
AU  - Hai-ping Huang
PY  - 2017/07
DA  - 2017/07
TI  - An Empirical Analysis of W&R Based on Listed Companies' Investments in Vocational Education
BT  - Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
PB  - Atlantis Press
SP  - 257
EP  - 262
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.45
DO  - 10.2991/iccse-17.2017.45
ID  - Huang2017/07
ER  -