Exploration of salience theory to deep learning: evidence from Chinese new energy market high-frequency trading
Authors:
- Qing ZhuQZQing Zhu
- Jinhong DuJDJinhong Du
- Yuze LiYLYuze Li
Open Access
- 1 September 2025
- journal article
- Published by KEAI Publishing in Data Science and Management
- Vol. 8 (3) , 296-309
Abstract
No abstract availableFunding Information
- National Natural Science Foundation of China (72032006, 92146005)
This publication has 38 references indexed in Scilit:
- Audiovisual speech recognition based on a deep convolutional neural networkData Science and Management, 2024
- Forecasting hourly PM2.5 concentrations based on decomposition-ensemble-reconstruction framework incorporating deep learning algorithmsData Science and Management, 2023
- A new prediction NN framework design for individual stock based on the industry environmentData Science and Management, 2022
- Host load prediction in cloud computing with Discrete Wavelet Transformation (DWT) and Bidirectional Gated Recurrent Unit (BiGRU) networkComputer Communications, 2022
- Financing SMEs and business development as new post Covid-19 economic recovery determinantsEconomic Analysis and Policy, 2022
- Salience theory and enhancing momentum profitsFinance Research Letters, 2022
- Attention and salience in preference reversalsExperimental Economics, 2022
- A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock ForecastingAnnals of Data Science, 2021
- Review on Convolutional Neural Networks (CNN) in vegetation remote sensingISPRS Journal of Photogrammetry and Remote Sensing, 2021
- Deep Learning Forecasting in Cryptocurrency High-Frequency TradingCognitive Computation, 2021