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

Empirical Analysis of RSI Based on Vocational Education Sector of Listed Companies

Authors
Fang Yu
Corresponding Author
Fang Yu
Available Online July 2017.
DOI
10.2991/iccse-17.2017.42How to use a DOI?
Keywords
Vocational education sector, RSI,Empirical analysis
Abstract

The paper tests the RSI expert system of securities trading software based on the real and open data from securities vocational education sector through the statistical empirical analysis. It makes empirical analysis of RSI anti trend index with annual net profit rate, rate of return and win rate as the management objective and the theory of mathematical statistics as the research basis, and obtains the result that the annual rate of return and net profit margin of RSI expert system were 44.4% and 44.3% of Shanghai Composite Index. 100% win rate and 4.76 times annual rate of return of annual interest rate on bank deposits provide a safe investment plan for investors. This result is obviously acceptable.

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-17.2017.42
ISSN
2352-538X
DOI
10.2991/iccse-17.2017.42How 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  - Fang Yu
PY  - 2017/07
DA  - 2017/07
TI  - Empirical Analysis of RSI Based on Vocational Education Sector of Listed Companies
BT  - Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
PB  - Atlantis Press
SP  - 237
EP  - 240
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.42
DO  - 10.2991/iccse-17.2017.42
ID  - Yu2017/07
ER  -