Research on Stock Return Forecasting Methods based on Time Series Models

Author:

Jiang Xiyuan

Abstract

Accurately predicting the trend of stock return rate is a hot research issue. With the development of artificial intelligence, machine learning, big data and other technologies, it brings new potential to the prediction of the stock market. In order to accurately predict the trend of stock return, this paper mainly constructs the time series ARMA model and random forest model, uses the stacking method to fuse the models, and predicts the daily return of Yangtze River Electric Power stock. The final fusion model has an MSE of 1.757 on the training set and 1.274 on the test set. The overall prediction error of the model is within an acceptable range. At the same time, the fused model can weaken the problem of underfitting of a single model, which provides a valuable reference for model optimization research.

Publisher

Boya Century Publishing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3