Implementations of Hybrid Prediction Models for Stock Price Forecasting

Jiaji Zeng

2024

Abstract

With the rapid advance of the world economy since the 20th century, many people are devoting their energy to studying the stock market for profit. Therefore, various research methods for stock price prediction have emerged, among which a single prediction model is an important part of these research methods. However, with the progress of technology, the limitations of single model prediction are gradually amplified. It is difficult to fully capture the dynamic changes and uncertainties of complex financial systems. So, aiming to augment the accuracy and reliability of predictions, scientists began exploring the possibility of combining multiple prediction models, namely hybrid prediction models. This research will start with stock price prediction, based on variable analysis, representative configuration, model application results and performance, as well as its limitations and prospects, to explore the implementation of hybrid prediction models for the prediction of stock price. These results are of great significance in exploring the development prospects, risk assessment, optimization and adjustment of financial markets.

Paper Citation

in Harvard Style

Zeng J. (2024). Implementations 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 568-573. DOI: 10.5220/0013270700004568

in Bibtex Style

@conference{ecai24,
author={Jiaji Zeng},
title={Implementations 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={568-573},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013270700004568},
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 - Implementations of Hybrid Prediction Models for Stock Price Forecasting
SN - 978-989-758-726-9
AU - Zeng J.
PY - 2024
SP - 568
EP - 573
DO - 10.5220/0013270700004568
PB - SciTePress