The Prediction and Analysis of Hyper-Parameter for Stock Market Prediction Based on GRU

Ziyi Jia

2023

Abstract

Stock market prediction has a crucial place in investment, risk management, and economic policy. Recently, the rise of deep learning has led to the use of advanced techniques such as neural networks, which have significantly improved the accuracy of stock market predictions and the ability to process complex data. In this research, the gated recurrent unit (GRU) model is constructed in-house for data analysis and mathematical modeling. Meanwhile, feature selection and loss functions are introduced to optimize the model. In addition, the results of the model’s predictions are visualized against real data, which helps to evaluate and improve the performance. Simultaneously, this study delved into the application of evaluation metrics through exploratory data analysis. Experimental results indicate that the model exhibits strong performance in the field of stock market prediction. The utilization of GRU models in stock price prediction holds significant implications for individuals, businesses, and financial institutions, as they provide critical market outlooks that support financial and economic decision-making across multiple domains, improve forecasting accuracy compared to traditional methods, and help all parties to better address market challenges and opportunities.

Paper Citation

in Harvard Style

Jia Z. (2023). The Prediction and Analysis of Hyper-Parameter for Stock Market Prediction Based on GRU. In Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-705-4, SciTePress, pages 75-80. DOI: 10.5220/0012798900003885

in Bibtex Style

@conference{daml23,
author={Ziyi Jia},
title={The Prediction and Analysis of Hyper-Parameter for Stock Market Prediction Based on GRU},
booktitle={Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2023},
pages={75-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012798900003885},
isbn={978-989-758-705-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - The Prediction and Analysis of Hyper-Parameter for Stock Market Prediction Based on GRU
SN - 978-989-758-705-4
AU - Jia Z.
PY - 2023
SP - 75
EP - 80
DO - 10.5220/0012798900003885
PB - SciTePress