Stock Indexes Forecasting Based on CNN-GRU-XGBOOST Hybrid Model-Reference-Cited by-同舟云学术

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Stock Indexes Forecasting Based on CNN-GRU-XGBOOST Hybrid Model

Published:2024-04-19 Issue: Volume:2014 Page:195-200
ISSN:
Container-title:Proceedings of the 2024 International Academic Conference on Edge Computing, Parallel and Distributed Computing
language:
Short-container-title:

Author:

Zhu Wei¹^ORCID,Hu QingChun¹^ORCID,Wang MingCheng¹^ORCID,Hu Kai¹^ORCID

Affiliation:

1. East China University of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3677404.3677438

Reference14 articles.

1. Predicting stock price movement using a DBN-RNN

2. Deep learning for finance: deep portfolios

3. Stock market forecasting using DRAGAN and feature matching

4. Sneha S Bagalkot and Dinesha H A and Nagaraj Naik. Novel grey wolf optimizer based parameters selection for GARCH and ARIMA models for stock price prediction.[J]. PeerJ. Computer science, 2024, 10: e1735-e1735.

5. Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction;Ariyo A. Ayodele;Journal of Applied Mathematics,2014

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