Application of ARIMA Model in Financial Time Series in Stocks

In order to study the development of stock exchange between China and the United States during the Sino-U.S. trade war, the stock trends of the two countries were compared and analyzed, combined with the time series prediction, and displayed with the visual result chart. Judging the data’s stability...

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Main Authors: Jiajia Cheng, Huiyun Deng, Guang Sun, Peng Guo, Jianjun Zhang
Format: Article
Language:English
Published: Springer, Cham 2020
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/26269/1/Application%20of%20ARIMA%20Model%20in%20Financial%20Time%20Series%20in%20Stocks.pdf
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author Jiajia Cheng
Huiyun Deng
Guang Sun
Peng Guo
Jianjun Zhang
author_facet Jiajia Cheng
Huiyun Deng
Guang Sun
Peng Guo
Jianjun Zhang
author_sort Jiajia Cheng
collection UMS
description In order to study the development of stock exchange between China and the United States during the Sino-U.S. trade war, the stock trends of the two countries were compared and analyzed, combined with the time series prediction, and displayed with the visual result chart. Judging the data’s stability from its original time sequence diagram, autocorrelation diagram and p-value, make difference for non-stationary data, then determine the appropriate parameters P and Q in ARIMA model according to autocorrelation diagram and partial autocorrelation diagram, confirm the model for model test, select the model with the lowest AIC, BIC and hqlc values to predict 10% of the total data and visualize. From the visual results, the prediction effect is not very good, there are relatively large errors, and the trend of stock closing price is not consistent. ARIMA model is not very good in the application of stock market, which needs to be improved.
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spelling ums.eprints-262692020-11-09T08:02:00Z https://eprints.ums.edu.my/id/eprint/26269/ Application of ARIMA Model in Financial Time Series in Stocks Jiajia Cheng Huiyun Deng Guang Sun Peng Guo Jianjun Zhang HB Economic theory. Demography In order to study the development of stock exchange between China and the United States during the Sino-U.S. trade war, the stock trends of the two countries were compared and analyzed, combined with the time series prediction, and displayed with the visual result chart. Judging the data’s stability from its original time sequence diagram, autocorrelation diagram and p-value, make difference for non-stationary data, then determine the appropriate parameters P and Q in ARIMA model according to autocorrelation diagram and partial autocorrelation diagram, confirm the model for model test, select the model with the lowest AIC, BIC and hqlc values to predict 10% of the total data and visualize. From the visual results, the prediction effect is not very good, there are relatively large errors, and the trend of stock closing price is not consistent. ARIMA model is not very good in the application of stock market, which needs to be improved. Springer, Cham 2020 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/26269/1/Application%20of%20ARIMA%20Model%20in%20Financial%20Time%20Series%20in%20Stocks.pdf Jiajia Cheng and Huiyun Deng and Guang Sun and Peng Guo and Jianjun Zhang (2020) Application of ARIMA Model in Financial Time Series in Stocks. Artificial Intelligence and Security. pp. 232-243. https://doi.org/10.1007/978-3-030-57884-8_21
spellingShingle HB Economic theory. Demography
Jiajia Cheng
Huiyun Deng
Guang Sun
Peng Guo
Jianjun Zhang
Application of ARIMA Model in Financial Time Series in Stocks
title Application of ARIMA Model in Financial Time Series in Stocks
title_full Application of ARIMA Model in Financial Time Series in Stocks
title_fullStr Application of ARIMA Model in Financial Time Series in Stocks
title_full_unstemmed Application of ARIMA Model in Financial Time Series in Stocks
title_short Application of ARIMA Model in Financial Time Series in Stocks
title_sort application of arima model in financial time series in stocks
topic HB Economic theory. Demography
url https://eprints.ums.edu.my/id/eprint/26269/1/Application%20of%20ARIMA%20Model%20in%20Financial%20Time%20Series%20in%20Stocks.pdf
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AT huiyundeng applicationofarimamodelinfinancialtimeseriesinstocks
AT guangsun applicationofarimamodelinfinancialtimeseriesinstocks
AT pengguo applicationofarimamodelinfinancialtimeseriesinstocks
AT jianjunzhang applicationofarimamodelinfinancialtimeseriesinstocks