Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework

Evolving simple and accurate symbolic regression models via asynchronous parallel computing

(2021) Aliyu Sani Sambo et al.   APPLIED SOFT COMPUTING

A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction

(2021) Nan Jing et al.   EXPERT SYSTEMS WITH APPLICATIONS

Forecasting directional movements of stock prices for intraday trading using LSTM and random forests

(2021) Pushpendu Ghosh et al.   Finance Research Letters

Forecasting stock prices with long-short term memory neural network based on attention mechanism

(2020) Jiayu Qiu et al.   PLoS One

A new financial data forecasting model using genetic algorithm and long short-term memory network

(2020) Yusheng Huang et al.   NEUROCOMPUTING

A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series

(2020) Seçkin Karasu et al.   ENERGY

Stock market forecasting with super-high dimensional time-series data using ConvLSTM, trend sampling, and specialized data augmentation

(2020) Si Woon Lee et al.   EXPERT SYSTEMS WITH APPLICATIONS

Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting

(2020) Yaoli Wang et al.   INFORMATION SCIENCES

CNNpred: CNN-based stock market prediction using a diverse set of variables

(2019) Ehsan Hoseinzade et al.   EXPERT SYSTEMS WITH APPLICATIONS

Knowledge distilling based model compression and feature learning in fault diagnosis

(2019) Wenfeng Zhang et al.   APPLIED SOFT COMPUTING

Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach

(2018) Omer Berat Sezer et al.   APPLIED SOFT COMPUTING

Deep learning with long short-term memory networks for financial market predictions

(2018) Thomas Fischer et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

A hybrid supervised semi-supervised graph-based model to predict one-day ahead movement of global stock markets and commodity prices

(2018) Arash Negahdari Kia et al.   EXPERT SYSTEMS WITH APPLICATIONS

ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module

(2018) Yujin Baek et al.   EXPERT SYSTEMS WITH APPLICATIONS

EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction

(2018) Feng Zhou et al.   EXPERT SYSTEMS WITH APPLICATIONS

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

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

(2017) Wei Bao et al.   PLoS One

Application of artificial neural network for the prediction of stock market returns: The case of the Japanese stock market

(2016) Mingyue Qiu et al.   CHAOS SOLITONS & FRACTALS

Evaluating machine learning classification for financial trading: An empirical approach

(2016) Eduardo A. Gerlein et al.   EXPERT SYSTEMS WITH APPLICATIONS

Bridging the divide in financial market forecasting: machine learners vs. financial economists

(2016) Ming-Wei Hsu et al.   EXPERT SYSTEMS WITH APPLICATIONS

Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction

(2016) Mustafa Göçken et al.   EXPERT SYSTEMS WITH APPLICATIONS

A Naïve SVM-KNN based stock market trend reversal analysis for Indian benchmark indices

(2015) Rudra Kalyan Nayak et al.   APPLIED SOFT COMPUTING

Stock trading rule discovery with an evolutionary trend following model

(2015) Yong Hu et al.   EXPERT SYSTEMS WITH APPLICATIONS

Sentiment analysis on social media for stock movement prediction

(2015) Thien Hai Nguyen et al.   EXPERT SYSTEMS WITH APPLICATIONS

Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks

(2015) Jie Wang et al.   NEUROCOMPUTING

Variable importance analysis: A comprehensive review

(2015) Pengfei Wei et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Design of experiments on neural network's parameters optimization for time series forecasting in stock markets

(2014) Mu-Yen Chen et al.   Neural Network World

Automated trading with performance weighted random forests and seasonality

(2013) Ash Booth et al.   EXPERT SYSTEMS WITH APPLICATIONS

A quantitative stock prediction system based on financial news

(2009) Robert P. Schumaker et al.   INFORMATION PROCESSING & MANAGEMENT

Development and performance evaluation of FLANN based model for forecasting of stock markets

(2008) Ritanjali Majhi et al.   EXPERT SYSTEMS WITH APPLICATIONS