Principe and Applications of Hybrid Prediction Models for Stock Price Forecasting

Yikun Liu

2024

Abstract

The stock market, one of the key elements of the financial industry, is a risky and lucrative arena that draws in a large number of traders. Contemporarily, there has been a surge in interest in research concerning stock price prediction. This research focuses on the concept and utilization of hybrid prediction models in predicting stock prices. This study first introduces some traditional and deep learning-based single models and the relevant background of stock forecasting, and then introduces some cutting-edge hybrid model configurations. The prediction results of these models were compared. By analysing mean average error (MAE), root mean square error (RMSE) and other performance metrics, it can be found that these hybrid models have a great improvement compared with the single model, and different models have different advantages. The research on hybrid model stock forecasting is helpful to understand its application in the stock market, better forecast stocks, and lay the foundation for the establishment of more diversified and effective models in the future.

Paper Citation

in Harvard Style

Liu Y. (2024). Principe and Applications of Hybrid Prediction Models for Stock Price Forecasting. In Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI; ISBN 978-989-758-726-9, SciTePress, pages 561-567. DOI: 10.5220/0013270600004568

in Bibtex Style

@conference{ecai24,
author={Yikun Liu},
title={Principe and Applications of Hybrid Prediction Models for Stock Price Forecasting},
booktitle={Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI},
year={2024},
pages={561-567},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013270600004568},
isbn={978-989-758-726-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on E-commerce and Artificial Intelligence - Volume 1: ECAI
TI - Principe and Applications of Hybrid Prediction Models for Stock Price Forecasting
SN - 978-989-758-726-9
AU - Liu Y.
PY - 2024
SP - 561
EP - 567
DO - 10.5220/0013270600004568
PB - SciTePress