Predicting Apple Inc. Stock Prices Using Machine Learning Techniques

Yuanchen Wang

2025

Abstract

The accurate prediction of financial asset prices is essential to the finance industry, where decisions rely heavily on future price forecasting. Using machine learning methods to forecast future closing values of financial assets is examined in this study. To improve resilience and forecast accuracy, this research integrates individual models like as Random Forest, Linear Regression, and Extreme Gradient Boosting (XGBoost) with ensemble methods like voting classifiers. Metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), and R^2 Score are employed to assess the models' effectiveness after they have been trained on historical data. Additionally, in order to produce a more reliable forecast, this study proposes a combined model technique that combines forecasts from several models. This paper aims to explore and optimize the combined application of different machine learning models to provide a more reliable decision support tool for financial market analysis, and ultimately provide investors and financial analysts with more forward-looking market insights.

Paper Citation

in Harvard Style

Wang Y. (2025). Predicting Apple Inc. Stock Prices Using Machine Learning Techniques. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 455-461. DOI: 10.5220/0013699300004670

in Bibtex Style

@conference{icdse25,
author={Yuanchen Wang},
title={Predicting Apple Inc. Stock Prices Using Machine Learning Techniques},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={455-461},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013699300004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Predicting Apple Inc. Stock Prices Using Machine Learning Techniques
SN - 978-989-758-765-8
AU - Wang Y.
PY - 2025
SP - 455
EP - 461
DO - 10.5220/0013699300004670
PB - SciTePress