Progress and prospects of data-driven stock price forecasting research
With the rapid development of social economy and the continuous improvement of stock market, stock investment has become more and more widely concerned. Stock price prediction has become an important research direction in the field of cognitive computing in engineering. Data-driven stock price forec...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2023-06-01
|
Series: | International Journal of Cognitive Computing in Engineering |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666307423000116 |
_version_ | 1797377865960914944 |
---|---|
author | Chuanjun Zhao Meiling Wu Jingfeng Liu Zening Duan Jie li Lihua Shen Xuekui Shangguan Donghang Liu Yanjie Wang |
author_facet | Chuanjun Zhao Meiling Wu Jingfeng Liu Zening Duan Jie li Lihua Shen Xuekui Shangguan Donghang Liu Yanjie Wang |
author_sort | Chuanjun Zhao |
collection | DOAJ |
description | With the rapid development of social economy and the continuous improvement of stock market, stock investment has become more and more widely concerned. Stock price prediction has become an important research direction in the field of cognitive computing in engineering. Data-driven stock price forecasting aims to predict future stock price trends based on historical values and textual data, which can effectively help people reduce risks and improve returns in the process of stock investment. The article reviews the literature on stock price forecasting methods, and classifies stock price forecasting methods from two different perspectives of model and feature. According to different model angles, the existing stock price prediction methods can be divided into statistical analysis methods, traditional machine learning methods and deep learning methods. According to different characteristic angles, the existing stock price prediction methods can be divided into those based on numerical data and those based on text mixed with numerical data. Finally, we summarize the research challenges faced by stock price prediction and provide future research directions. |
first_indexed | 2024-03-08T19:58:33Z |
format | Article |
id | doaj.art-c61f598d58b34f719c9f5b29bbc6f93d |
institution | Directory Open Access Journal |
issn | 2666-3074 |
language | English |
last_indexed | 2024-03-08T19:58:33Z |
publishDate | 2023-06-01 |
publisher | KeAi Communications Co., Ltd. |
record_format | Article |
series | International Journal of Cognitive Computing in Engineering |
spelling | doaj.art-c61f598d58b34f719c9f5b29bbc6f93d2023-12-24T04:46:38ZengKeAi Communications Co., Ltd.International Journal of Cognitive Computing in Engineering2666-30742023-06-014100108Progress and prospects of data-driven stock price forecasting researchChuanjun Zhao0Meiling Wu1Jingfeng Liu2Zening Duan3Jie li4Lihua Shen5Xuekui Shangguan6Donghang Liu7Yanjie Wang8Corresponding author.; School of Information, Shanxi University of Finance and Economics, Taiyuan, 030006, Shanxi, China; Financial Innovation and Big Data Statistical Analysis Laboratory, Shanxi University of Finance and Economics, Taiyuan, 030006, Shanxi, ChinaSchool of Information, Shanxi University of Finance and Economics, Taiyuan, 030006, Shanxi, ChinaSchool of Information, Shanxi University of Finance and Economics, Taiyuan, 030006, Shanxi, ChinaSchool of Journalism and Mass Communication, University of Wisconsin-Madison, Madison, 53706, WI, USASchool of Information, Shanxi University of Finance and Economics, Taiyuan, 030006, Shanxi, ChinaShanxi Information Technology Application Innovation Engineering Research Center, Taiyuan, 030006, Shanxi, ChinaShanxi Information Technology Application Innovation Engineering Research Center, Taiyuan, 030006, Shanxi, ChinaShanxi Information Technology Application Innovation Engineering Research Center, Taiyuan, 030006, Shanxi, ChinaShanxi Information Technology Application Innovation Engineering Research Center, Taiyuan, 030006, Shanxi, ChinaWith the rapid development of social economy and the continuous improvement of stock market, stock investment has become more and more widely concerned. Stock price prediction has become an important research direction in the field of cognitive computing in engineering. Data-driven stock price forecasting aims to predict future stock price trends based on historical values and textual data, which can effectively help people reduce risks and improve returns in the process of stock investment. The article reviews the literature on stock price forecasting methods, and classifies stock price forecasting methods from two different perspectives of model and feature. According to different model angles, the existing stock price prediction methods can be divided into statistical analysis methods, traditional machine learning methods and deep learning methods. According to different characteristic angles, the existing stock price prediction methods can be divided into those based on numerical data and those based on text mixed with numerical data. Finally, we summarize the research challenges faced by stock price prediction and provide future research directions.http://www.sciencedirect.com/science/article/pii/S2666307423000116Stock price forecastingTime seriesMachine learningNumerical and textual dataResearch review |
spellingShingle | Chuanjun Zhao Meiling Wu Jingfeng Liu Zening Duan Jie li Lihua Shen Xuekui Shangguan Donghang Liu Yanjie Wang Progress and prospects of data-driven stock price forecasting research International Journal of Cognitive Computing in Engineering Stock price forecasting Time series Machine learning Numerical and textual data Research review |
title | Progress and prospects of data-driven stock price forecasting research |
title_full | Progress and prospects of data-driven stock price forecasting research |
title_fullStr | Progress and prospects of data-driven stock price forecasting research |
title_full_unstemmed | Progress and prospects of data-driven stock price forecasting research |
title_short | Progress and prospects of data-driven stock price forecasting research |
title_sort | progress and prospects of data driven stock price forecasting research |
topic | Stock price forecasting Time series Machine learning Numerical and textual data Research review |
url | http://www.sciencedirect.com/science/article/pii/S2666307423000116 |
work_keys_str_mv | AT chuanjunzhao progressandprospectsofdatadrivenstockpriceforecastingresearch AT meilingwu progressandprospectsofdatadrivenstockpriceforecastingresearch AT jingfengliu progressandprospectsofdatadrivenstockpriceforecastingresearch AT zeningduan progressandprospectsofdatadrivenstockpriceforecastingresearch AT jieli progressandprospectsofdatadrivenstockpriceforecastingresearch AT lihuashen progressandprospectsofdatadrivenstockpriceforecastingresearch AT xuekuishangguan progressandprospectsofdatadrivenstockpriceforecastingresearch AT donghangliu progressandprospectsofdatadrivenstockpriceforecastingresearch AT yanjiewang progressandprospectsofdatadrivenstockpriceforecastingresearch |