The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index

Renhao Jin; Sha Wang; Fang Yan; Jie Zhu

doi:doi:10.11648/j.sjams.20150304.16

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The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index

Renhao Jin, Sha Wang, Fang Yan, Jie Zhu

Published in Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 4)

Received: 30 June 2015 Accepted: 27 July 2015 Published: 5 August 2015

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Abstract

In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 3, Issue 4)
DOI	10.11648/j.sjams.20150304.16
Page(s)	199-203
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

The Shanghai Composite Stock Price Index (SCSPI), Prediction, ARIMA Model

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APA Style

Renhao Jin, Sha Wang, Fang Yan, Jie Zhu. (2015). The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Science Journal of Applied Mathematics and Statistics, 3(4), 199-203. https://doi.org/10.11648/j.sjams.20150304.16

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ACS Style

Renhao Jin; Sha Wang; Fang Yan; Jie Zhu. The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Sci. J. Appl. Math. Stat. 2015, 3(4), 199-203. doi: 10.11648/j.sjams.20150304.16

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AMA Style

Renhao Jin, Sha Wang, Fang Yan, Jie Zhu. The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Sci J Appl Math Stat. 2015;3(4):199-203. doi: 10.11648/j.sjams.20150304.16

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@article{10.11648/j.sjams.20150304.16,
  author = {Renhao Jin and Sha Wang and Fang Yan and Jie Zhu},
  title = {The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {3},
  number = {4},
  pages = {199-203},
  doi = {10.11648/j.sjams.20150304.16},
  url = {https://doi.org/10.11648/j.sjams.20150304.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150304.16},
  abstract = {In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.},
 year = {2015}
}

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TY  - JOUR
T1  - The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index
AU  - Renhao Jin
AU  - Sha Wang
AU  - Fang Yan
AU  - Jie Zhu
Y1  - 2015/08/05
PY  - 2015
N1  - https://doi.org/10.11648/j.sjams.20150304.16
DO  - 10.11648/j.sjams.20150304.16
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 199
EP  - 203
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20150304.16
AB  - In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.
VL  - 3
IS  - 4
ER  -

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Author Information

Renhao Jin

School of Information, Beijing Wuzi University, Beijing, China
Sha Wang

School of Information, Beijing Wuzi University, Beijing, China
Fang Yan

School of Information, Beijing Wuzi University, Beijing, China
Jie Zhu

School of Information, Beijing Wuzi University, Beijing, China

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APA Style

Renhao Jin, Sha Wang, Fang Yan, Jie Zhu. (2015). The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Science Journal of Applied Mathematics and Statistics, 3(4), 199-203. https://doi.org/10.11648/j.sjams.20150304.16

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ACS Style

Renhao Jin; Sha Wang; Fang Yan; Jie Zhu. The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Sci. J. Appl. Math. Stat. 2015, 3(4), 199-203. doi: 10.11648/j.sjams.20150304.16

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AMA Style

Renhao Jin, Sha Wang, Fang Yan, Jie Zhu. The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index. Sci J Appl Math Stat. 2015;3(4):199-203. doi: 10.11648/j.sjams.20150304.16

Copy | Download

@article{10.11648/j.sjams.20150304.16,
  author = {Renhao Jin and Sha Wang and Fang Yan and Jie Zhu},
  title = {The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {3},
  number = {4},
  pages = {199-203},
  doi = {10.11648/j.sjams.20150304.16},
  url = {https://doi.org/10.11648/j.sjams.20150304.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20150304.16},
  abstract = {In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - The Application of ARIMA Model in 2014 Shanghai Composite Stock Price Index
AU  - Renhao Jin
AU  - Sha Wang
AU  - Fang Yan
AU  - Jie Zhu
Y1  - 2015/08/05
PY  - 2015
N1  - https://doi.org/10.11648/j.sjams.20150304.16
DO  - 10.11648/j.sjams.20150304.16
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 199
EP  - 203
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20150304.16
AB  - In order to study the changes of Shanghai Composite Stock Price Index (SCSPI) and predict the trend of stock market fluctuations, this paper constructed a time-series analysis．A non-stationary trend is found, and an ARIMA model is found to sufficiently model the data. A short trend of Shanghai composite stock price index is then predicted using the established model.
VL  - 3
IS  - 4
ER  -

Copy | Download