Bilateral Autotrading Framework for Stock Prediction
2021 International Joint Conference on Neural Networks (IJCNN)（2021）
摘要
As the core of quantitative trading, indicator effectiveness continuously plays a vital role in stock prediction. The majority of studies are currently dedicated to constructing indicators with high Pearson Correlation Coefficient (CORR) with returns. However, the pursuit of high CORR may ignore some indicators that produce high profits. Therefore, we propose a new Bilateral Correlation Coefficien...
更多查看译文
关键词
Correlation coefficient,Profitability,Neural networks,Prediction methods,Transformers,Stock markets,Optimization
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要