Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
出版年份 2021 全文链接
标题
Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process
作者
关键词
Genetic algorithm, XGBoost feature selection, Technical indicators, Blessing of dimensionality, Curse of dimensionality, Feature set expansion, Optimal feature set
出版物
EXPERT SYSTEMS WITH APPLICATIONS
Volume 186, Issue -, Pages 115716
出版商
Elsevier BV
发表日期
2021-08-13
DOI
10.1016/j.eswa.2021.115716
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- An integrated framework of deep learning and knowledge graph for prediction of stock price trend: An application in Chinese stock exchange market
- (2020) Jiawei Long et al. APPLIED SOFT COMPUTING
- An efficient XGBoost–DNN-based classification model for network intrusion detection system
- (2020) Preethi Devan et al. NEURAL COMPUTING & APPLICATIONS
- Deep Learning for Stock Market Prediction
- (2020) M. Nabipour et al. Entropy
- Predicting the Trend of Stock Market Index Using the Hybrid Neural Network Based on Multiple Time Scale Feature Learning
- (2020) Yaping Hao et al. Applied Sciences-Basel
- Literature Review: Machine Learning Techniques Applied to Financial Market Prediction
- (2019) Bruno Miranda Henrique et al. EXPERT SYSTEMS WITH APPLICATIONS
- An XGBoost-based physical fitness evaluation model using advanced feature selection and Bayesian hyper-parameter optimization for wearable running monitoring
- (2019) Junqi Guo et al. Computer Networks
- Genetic algorithm-optimized multi-channel convolutional neural network for stock market prediction
- (2019) Hyejung Chung et al. NEURAL COMPUTING & APPLICATIONS
- Stock price prediction based on deep neural networks
- (2019) Pengfei Yu et al. NEURAL COMPUTING & APPLICATIONS
- Combining Principal Component Analysis, Discrete Wavelet Transform and XGBoost to trade in the financial markets
- (2019) João Nobre et al. EXPERT SYSTEMS WITH APPLICATIONS
- A systematic review of fundamental and technical analysis of stock market predictions
- (2019) Isaac Kofi Nti et al. ARTIFICIAL INTELLIGENCE REVIEW
- Study on the prediction of stock price based on the associated network model of LSTM
- (2019) Guangyu Ding et al. International Journal of Machine Learning and Cybernetics
- Methods for interpreting and understanding deep neural networks
- (2018) Grégoire Montavon et al. DIGITAL SIGNAL PROCESSING
- On the Reduction of Computational Complexity of Deep Convolutional Neural Networks
- (2018) Partha Maji et al. Entropy
- DeepClue: Visual Interpretation of Text-based Deep Stock Prediction
- (2018) Lei Shi et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Combining the wisdom of crowds and technical analysis for financial market prediction using deep random subspace ensembles
- (2018) Qili Wang et al. NEUROCOMPUTING
- Blessing of dimensionality: mathematical foundations of the statistical physics of data
- (2018) A. N. Gorban et al. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
- Statistical and Machine Learning forecasting methods: Concerns and ways forward
- (2018) Spyros Makridakis et al. PLoS One
- A study on novel filtering and relationship between input-features and target-vectors in a deep learning model for stock price prediction
- (2018) Yoojeong Song et al. APPLIED INTELLIGENCE
- Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction
- (2018) Hyejung Chung et al. Sustainability
- A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction
- (2017) Yingjun Chen et al. EXPERT SYSTEMS WITH APPLICATIONS
- Fast-mRMR: Fast Minimum Redundancy Maximum Relevance Algorithm for High-Dimensional Big Data
- (2016) Sergio Ramírez-Gallego et al. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
- Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model
- (2016) Mingyue Qiu et al. PLoS One
- Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques
- (2015) Jigar Patel et al. EXPERT SYSTEMS WITH APPLICATIONS
- Evaluating multiple classifiers for stock price direction prediction
- (2015) Michel Ballings et al. EXPERT SYSTEMS WITH APPLICATIONS
- A GA-based feature selection approach with an application to handwritten character recognition
- (2013) C. De Stefano et al. PATTERN RECOGNITION LETTERS
- Intelligent stock trading system based on improved technical analysis and Echo State Network
- (2011) Xiaowei Lin et al. EXPERT SYSTEMS WITH APPLICATIONS
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