Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process

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