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September 10, 2025Bulletin of Electrical Engineering and InformaticsOpen Access

Prediction of stock market price for investors using machine learning approach

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Authors

OEOmobayo Ayokunle EsanDEDorcas Oladayo EsanFEFemi Abiodun Elegbeleye

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Overview

Proposed model integrates logistic regression and support vector machine, showing improved accuracy in financial decision-making.

Key Points

  • The proposed hybrid model achieved an accuracy of 98.86% on the Dhaka dataset, illustrating its effectiveness.
  • Results demonstrate improved performance in root mean square error (RMSE) and mean absolute percentage error (MAPE) compared to traditional models.
  • The approach combines logistic regression's interpretability with support vector machine's robustness to analyze stock market data.
  • Using publicly available Yahoo Finance datasets, the model facilitates better investment decision-making through enhanced prediction capabilities.

Cite This Study

Esan et al. (2025) studied this question.

synapsesocial.com/papers/68c1b81254b1d3bfb60ebe3ehttps://doi.org/10.11591/eei.v14i4.8971
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