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

Comparative Analysis of Cloud Computing Sector Based on Listed Companies

Authors
Ni Ruan, Hai-ping Huang, Huan Deng
Corresponding Author
Ni Ruan
Available Online July 2017.
DOI
10.2991/iccse-17.2017.48How to use a DOI?
Keywords
Cloud computing, MA,MACD, Comparative analysis
Abstract

This paper tested the MACD and MA expert systems of securities trading software with the statistical empirical analysis method based on the real and open securities cloud computing sector data. And it also conducted a comparative analysis of the MACD and MA trend indicators based on the theory of mathematical statistics with the annual net profit margin, rate of return and winning percentage as the management objectives. The results showed that annual rate of return and net profit margin of the MACD expert system was 215.41% and 215.25% of that of the MA expert system respectively, and the risk of the two expert systems was almost the same. Investors should choose the MACD expert system for the cloud computing sector.

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/).

Download article (PDF)

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-17.2017.48
ISSN
2352-538X
DOI
10.2991/iccse-17.2017.48How 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  - Ni Ruan
AU  - Hai-ping Huang
AU  - Huan Deng
PY  - 2017/07
DA  - 2017/07
TI  - Comparative Analysis of Cloud Computing Sector Based on Listed Companies
BT  - Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
PB  - Atlantis Press
SP  - 274
EP  - 278
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.48
DO  - 10.2991/iccse-17.2017.48
ID  - Ruan2017/07
ER  -