Empirical evaluation of an automated intraday stock recommendation system incorporating both market data and textual news

Keyphrases

• Data Market 100%
• Stock Recommendations 100%
• Recommendation System 100%
• Data Representation 80%
• News Data 40%
• Economic Evaluation 40%
• Text Data 40%
• Forecasting Algorithm 40%
• Two-source 20%
• Transaction Costs 20%
• Intraday Trading 20%
• Performance Criteria 20%
• Stock Purchase 20%
• Forecasting Model 20%
• Recommendation Evaluation 20%
• Recommendation Process 20%
• Simulation Procedure 20%
• Purchase Decision 20%
• Data Preprocessing 20%
• Word Count 20%
• Neural Network Prediction 20%
• Joint Pattern 20%
• Sentiment Analysis 20%
• Stock Investment 20%
• Big Data Mining 20%
• Stock Return Prediction 20%
• Model Validation 20%
• Human Bias 20%
• Nonlinear Neural Networks 20%
• Investment Recommendation 20%
• Modeling Process 20%
• Simple Representation 20%
• Data Mining Techniques 20%
• Incremental Value 20%

Computer Science

• Data Representation 100%
• Data Mining 50%
• Performance Criterion 25%
• Large Scale Data 25%
• Modeling Process 25%
• Data Preprocessing 25%
• Data Mining Technique 25%
• Purchase Decision 25%
• Neural Network 25%
• Sentiment Analysis 25%
• Data Source 25%
• Simple Representation 25%
• Human Bias 25%