Capturing dynamics of post-earnings-announcement drift using a genetic algorithm-optimized XGBoost

作者：

Highlights：

• Predict cumulative abnormal return of stocks following earnings release using XGBoost.

• Study drivers of post-earnings-release drift (PEAD) as identified by XGBoost.

• Remedy the difficulty of buying into a moving market when trading on PEAD signals.

摘要

•Predict cumulative abnormal return of stocks following earnings release using XGBoost.•Study drivers of post-earnings-release drift (PEAD) as identified by XGBoost.•Remedy the difficulty of buying into a moving market when trading on PEAD signals.

论文关键词：Post-earnings-announcement drift,XGBoost,Genetic algorithm,Financial trading

论文评审过程：Received 26 September 2020, Revised 6 March 2021, Accepted 6 March 2021, Available online 16 March 2021, Version of Record 8 April 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114892