Stock Price Prediction Using Stepwise Regression and Improved with Factor Analysis

Qiang Dai; Yantong Liu; Kaiyin Cai; Chunlin Jia

doi:10.54254/2754-1169/22/20230283

Research Article

Open access

Published on 13 September 2023

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Dai,Q.;Liu,Y.;Cai,K.;Jia,C. (2023). Stock Price Prediction Using Stepwise Regression and Improved with Factor Analysis. Advances in Economics, Management and Political Sciences,22,30-41.

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Stock Price Prediction Using Stepwise Regression and Improved with Factor Analysis

Qiang Dai *^,1, Yantong Liu ², Kaiyin Cai ³, Chunlin Jia ⁴

¹ University of International Business and Economics
² City University of Macau
³ University of Jimei
⁴ University of Shandong Technology and Business

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/22/20230283

Abstract

Owing to volatility in stock markets, it is quite elusive to forecast stock prices. Albeit, sometimes regular patterns are manifested in stock prices and a variety of factors are proved to be competent to determine stock prices partly. Hence, using stepwise regression on historical stock price data, this paper proposes determining similar patterns in stock prices and exploring potential rules to select the main factors that can affect stock prices significantly while taking all factors into account. Difference analysis is also employed to probe possible correlations in the data. Eventually, this paper tries to improve stock price prediction using factor analysis and manages to achieve higher accuracy.

Keywords

stock price prediction, stepwise regression, comparison analysis, factor analysis

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References

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Cite this article

Dai,Q.;Liu,Y.;Cai,K.;Jia,C. (2023). Stock Price Prediction Using Stepwise Regression and Improved with Factor Analysis. Advances in Economics, Management and Political Sciences,22,30-41.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Management Research and Economic Development

Conference website: https://2023.icmred.org/

ISBN：978-1-915371-87-4(Print) / 978-1-915371-88-1(Online)

Conference date: 28 April 2023

Editor：Canh Thien Dang, Javier Cifuentes-Faura

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.22

ISSN：2754-1169(Print) / 2754-1177(Online)

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