Empirical Analysis of MACD Based on Cloud Computing of Listed Companies

DOI

10.2991/iccse-17.2017.40How to use a DOI?

Keywords

Cloud computing, MACD, Empirical analysis

Abstract

MACD (Moving Average Convergence and Divergence), as an expert system of software for securities trading, is tested by statistical and empirical analysis based on real data about cloud computing which are publicly available. To realize management objectives of annual net profit margin, rate of return and win rate, non-directional MACD indicators are empirically analyzed based on theories of mathematical statistics. In this expert system, annual rate of return and net profit margin are 102.08% and 102.07% of Shanghai Stock Exchange indexes respectively. An investment solution will be optional for investors who prefer making considerable profits and dare to take risks as long as their win rate is as high as 45.53% and their annual rate of return is 11.85 times the annual interest rate of bank deposits.

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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TY  - CONF
AU  - Pin Wang
AU  - Zhong-hua Ling
AU  - Hong Li
PY  - 2017/07
DA  - 2017/07
TI  - Empirical Analysis of MACD Based on Cloud Computing of Listed Companies
BT  - Proceedings of the 2017 International Conference on Computational Science and Engineering (ICCSE 2017)
PB  - Atlantis Press
SP  - 222
EP  - 226
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccse-17.2017.40
DO  - 10.2991/iccse-17.2017.40
ID  - Wang2017/07
ER  -