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Forecasting daily stock market return using dimensionality reduction

Expert systems with applications, 2017-01, Vol.67, p.126-139

2017

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Predicting the daily return direction of the stock market using hybrid machine learning algorithms

Financial innovation (Heidelberg), 2019-06, Vol.5 (1), p.1-20, Article 24

2019

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The use of data mining and neural networks for forecasting stock market returns

Expert systems with applications, 2005-11, Vol.29 (4), p.927-940

2005

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Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared

Financial innovation (Heidelberg), 2024-08, Vol.10 (1), p.117-26, Article 117

2024

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Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry

Procedia computer science, 2017, Vol.114, p.242-249

2017

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A comprehensive cluster and classification mining procedure for daily stock market return forecasting

Neurocomputing (Amsterdam), 2017-12, Vol.267, p.152-168

2017

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Hedge fund replication using strategy specific factors

Financial innovation (Heidelberg), 2019-03, Vol.5 (1), p.1-19, Article 11

2019

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A machine learning trading system for the stock market based on N-period Min-Max labeling using XGBoost

Expert systems with applications, 2023-01, Vol.211, p.118581, Article 118581

2023

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A novel trading system for the stock market using Deep Q-Network action and instance selection

Expert systems with applications, 2024-12, Vol.257, p.125043, Article 125043

2024

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Selective genetic algorithm labeling: A new data labeling method for machine learning stock market trading systems

Engineering applications of artificial intelligence, 2024-09, Vol.135, p.108680, Article 108680

2024

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Developing a rule change trading system for the futures market using rough set analysis

Expert systems with applications, 2016-10, Vol.59, p.165-173

2016

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A dynamic target volatility strategy for asset allocation using artificial neural networks

The Engineering economist, 2018-10, Vol.63 (4), p.273-290

2018

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Volatility Forecasting Using a Hybrid GJR-GARCH Neural Network Model

Procedia computer science, 2014, Vol.36, p.246-253

2014

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An adaptive stock index trading decision support system

Expert systems with applications, 2016-10, Vol.59, p.195-207

2016

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Stock Market Prediction Using a Combination of Stepwise Regression Analysis, Differential Evolution-based Fuzzy Clustering, and a Fuzzy Inference Neural Network

Intelligent automation and soft computing, 2013-01, Vol.19 (4), p.636-648

2013

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Estimation of Earthquake Loss due to Bridge Damage in the St. Louis Metropolitan Area. II: Indirect Losses

Natural hazards review, 2008-02, Vol.9 (1), p.12-19

2008

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A hybrid stock trading system for intelligent technical analysis-based equivolume charting

Neurocomputing (Amsterdam), 2009-10, Vol.72 (16), p.3517-3528

2009

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Instance Selection Using Genetic Algorithms for an Intelligent Ensemble Trading System

Procedia computer science, 2017, Vol.114, p.465-472

2017

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Using Neural Networks to Forecast Volatility for an Asset Allocation Strategy Based on the Target Volatility

Procedia computer science, 2016, Vol.95, p.281-286

2016

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A relative value trading system based on a correlation and rough set analysis for the foreign exchange futures market

Engineering applications of artificial intelligence, 2017-05, Vol.61, p.47-56

2017

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Evaluating Forecasting Methods by Considering Different Accuracy Measures

Procedia computer science, 2016, Vol.95, p.264-271

2016

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Intelligent technical analysis based equivolume charting for stock trading using neural networks

Expert systems with applications, 2008-02, Vol.34 (2), p.1004-1017

2008

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An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms

Applied soft computing, 2017-06, Vol.55, p.127-140

2017

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Part IV: Business and Financial Analytics Preface

Procedia computer science, 2014, Vol.36, p.218-219

Enke, David

2014

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Interest rate prediction: a neuro-hybrid approach with data preprocessing

International journal of general systems, 2014-07, Vol.43 (5), p.535-550

2014

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Forecasting daily stock market return using dimensionality reduction

Predicting the daily return direction of the stock market using hybrid machine learning algorithms

The use of data mining and neural networks for forecasting stock market returns

Deep learning for Bitcoin price direction prediction: models and trading strategies empirically compared

Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry

A comprehensive cluster and classification mining procedure for daily stock market return forecasting

Hedge fund replication using strategy specific factors

A machine learning trading system for the stock market based on N-period Min-Max labeling using XGBoost

A novel trading system for the stock market using Deep Q-Network action and instance selection

Selective genetic algorithm labeling: A new data labeling method for machine learning stock market trading systems

Developing a rule change trading system for the futures market using rough set analysis

A dynamic target volatility strategy for asset allocation using artificial neural networks

Volatility Forecasting Using a Hybrid GJR-GARCH Neural Network Model

An adaptive stock index trading decision support system

Stock Market Prediction Using a Combination of Stepwise Regression Analysis, Differential Evolution-based Fuzzy Clustering, and a Fuzzy Inference Neural Network

Estimation of Earthquake Loss due to Bridge Damage in the St. Louis Metropolitan Area. II: Indirect Losses

A hybrid stock trading system for intelligent technical analysis-based equivolume charting

Instance Selection Using Genetic Algorithms for an Intelligent Ensemble Trading System

Using Neural Networks to Forecast Volatility for an Asset Allocation Strategy Based on the Target Volatility

A relative value trading system based on a correlation and rough set analysis for the foreign exchange futures market

Evaluating Forecasting Methods by Considering Different Accuracy Measures

Intelligent technical analysis based equivolume charting for stock trading using neural networks

An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms

Part IV: Business and Financial Analytics Preface

Interest rate prediction: a neuro-hybrid approach with data preprocessing

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