Concept drift mining of portfolio selection factors in stock market
作者：
Highlights：
• Provide a model based on causal discovery technique (ANMCPT) for concept drift mining in cross-sectional analysis.
• AVMCPT can discover causal in high-dimensional and dynamic environment.
• ANMCPT outperform the classical Fama–French framework.
• Concept drift phenomenon in China stock market is observed and exhibited clearly.
摘要
•Provide a model based on causal discovery technique (ANMCPT) for concept drift mining in cross-sectional analysis.•AVMCPT can discover causal in high-dimensional and dynamic environment.•ANMCPT outperform the classical Fama–French framework.•Concept drift phenomenon in China stock market is observed and exhibited clearly.
论文关键词：Concept drift mining,Stock analysis,Cross-sectional analysis,Causal discovery,Modified Additive Noise Model with Conditional Probability Table,China stock market
论文评审过程：Received 25 November 2014, Revised 19 May 2015, Accepted 14 June 2015, Available online 8 July 2015, Version of Record 7 December 2015.
论文官网地址：https://doi.org/10.1016/j.elerap.2015.06.002
