Study on the Fitness of ARIMA Model in Stock Forecasting

With the continuous development of the world’s financial industry, the international stock market trend prediction has now become one of the most closely related to the actual financial industry, with more and more scholars into the research, the accuracy of asset price prediction is constantly impr...

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Main Author: Li Jingwen
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:SHS Web of Conferences
Online Access:https://www.shs-conferences.org/articles/shsconf/pdf/2024/28/shsconf_dsm2024_01028.pdf
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author Li Jingwen
author_facet Li Jingwen
author_sort Li Jingwen
collection DOAJ
description With the continuous development of the world’s financial industry, the international stock market trend prediction has now become one of the most closely related to the actual financial industry, with more and more scholars into the research, the accuracy of asset price prediction is constantly improving. Technical analysis is one of the most important components of securities analysis methods. Among the many prediction models, choosing the most appropriate prediction model for modelling according to the specific objectives is twice as effective and has become the source of motivation for the development of this study. In this study, the ARIMA model, which is one of the most popular models in this field of research, is used to forecast two of the most representative assets in the international stock market. On this basis, the results are discussed and analysed to conclude that compared with the CSI300 index, the accuracy of the model’s prediction results for the SP500 is greater, which provides strong support and suggestions for the subsequent research on the two stocks, and also provides a valuable reference for the prediction of the current hot technology methods in the stock markets of different economies.
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institution Kabale University
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series SHS Web of Conferences
spelling doaj-art-74eafb443e0a4314999257df5fa3f9782024-12-13T10:11:01ZengEDP SciencesSHS Web of Conferences2261-24242024-01-012080102810.1051/shsconf/202420801028shsconf_dsm2024_01028Study on the Fitness of ARIMA Model in Stock ForecastingLi Jingwen0School of Mathematical Sciences, Tiangong UniversityWith the continuous development of the world’s financial industry, the international stock market trend prediction has now become one of the most closely related to the actual financial industry, with more and more scholars into the research, the accuracy of asset price prediction is constantly improving. Technical analysis is one of the most important components of securities analysis methods. Among the many prediction models, choosing the most appropriate prediction model for modelling according to the specific objectives is twice as effective and has become the source of motivation for the development of this study. In this study, the ARIMA model, which is one of the most popular models in this field of research, is used to forecast two of the most representative assets in the international stock market. On this basis, the results are discussed and analysed to conclude that compared with the CSI300 index, the accuracy of the model’s prediction results for the SP500 is greater, which provides strong support and suggestions for the subsequent research on the two stocks, and also provides a valuable reference for the prediction of the current hot technology methods in the stock markets of different economies.https://www.shs-conferences.org/articles/shsconf/pdf/2024/28/shsconf_dsm2024_01028.pdf
spellingShingle Li Jingwen
Study on the Fitness of ARIMA Model in Stock Forecasting
SHS Web of Conferences
title Study on the Fitness of ARIMA Model in Stock Forecasting
title_full Study on the Fitness of ARIMA Model in Stock Forecasting
title_fullStr Study on the Fitness of ARIMA Model in Stock Forecasting
title_full_unstemmed Study on the Fitness of ARIMA Model in Stock Forecasting
title_short Study on the Fitness of ARIMA Model in Stock Forecasting
title_sort study on the fitness of arima model in stock forecasting
url https://www.shs-conferences.org/articles/shsconf/pdf/2024/28/shsconf_dsm2024_01028.pdf
work_keys_str_mv AT lijingwen studyonthefitnessofarimamodelinstockforecasting