A Regression-Based Share Market Prediction Model for Bangladesh

Fuente: arXiv
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Main Authors: Fabiha, Syeda Tasnim, Mumu, Rubaiyat Jahan, Aktar, Farzana, Hossain, B M Mainul
Format: Preprint
Published: 2025
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_version_ 1866916862139301888
author Fabiha, Syeda Tasnim
Mumu, Rubaiyat Jahan
Aktar, Farzana
Hossain, B M Mainul
author_facet Fabiha, Syeda Tasnim
Mumu, Rubaiyat Jahan
Aktar, Farzana
Hossain, B M Mainul
contents Share market is one of the most important sectors of economic development of a country. Everyday almost all companies issue their shares and investors buy and sell shares of these companies. Generally investors want to buy shares of the companies whose market liquidity is comparatively greater. Market liquidity depends on the average price of a share. In this paper, a thorough linear regression analysis has been performed on the stock market data of Dhaka Stock Exchange. Later, the linear model has been compared with random forest based on different metrics showing better results for random forest model. However, the amount of individual significance of different factors on the variability of stock price has been identified and explained. This paper also shows that the time series data is not capable of generating a predictive linear model for analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2507_18643
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Regression-Based Share Market Prediction Model for Bangladesh
Fabiha, Syeda Tasnim
Mumu, Rubaiyat Jahan
Aktar, Farzana
Hossain, B M Mainul
Statistical Finance
Machine Learning
62J05, 62P20 62J05, 62P20 62J05, 62P20
I.2.6; J.1; J.4
Share market is one of the most important sectors of economic development of a country. Everyday almost all companies issue their shares and investors buy and sell shares of these companies. Generally investors want to buy shares of the companies whose market liquidity is comparatively greater. Market liquidity depends on the average price of a share. In this paper, a thorough linear regression analysis has been performed on the stock market data of Dhaka Stock Exchange. Later, the linear model has been compared with random forest based on different metrics showing better results for random forest model. However, the amount of individual significance of different factors on the variability of stock price has been identified and explained. This paper also shows that the time series data is not capable of generating a predictive linear model for analysis.
title A Regression-Based Share Market Prediction Model for Bangladesh
topic Statistical Finance
Machine Learning
62J05, 62P20 62J05, 62P20 62J05, 62P20
I.2.6; J.1; J.4
url https://arxiv.org/abs/2507.18643