基于DE-lightGBM模型的上市公司高送转预测实证研究

Empirical Study on the Forecast of Large Stock Dividends of Listed Companies Based on DE-lightGBM

“高送转”现象指上市公司转增较大比例的股票。针对上市公司实施“高送转”现象的预测问题,文中提出了一种基于差分进化算法超参数优化的lightGBM模型(简记为DE-lightGBM)。该模型主要包括两个方面:首先,利用差分进化算法调整lightGBM模型的损失函数中少数类别的权重以及正则项系数,以处理数据类别不平衡的问题;其次,以F1和AUC作为评价指标,再次利用差分进化算法优化li-ghtGBM模型的重要超参数变量,找到一组预测效果最优的参数组合。数值结果显示,DElightGBM模型取得了较好的效果,F1和AUC值分别为0.5368和0.8734。提出的DE-lightGBM模型能够有效识别下一年将会实施“高送转”的上市公司。

Large stock dividends refers to the transfer of a large proportion of shares by listed companies.Aiming at the prediction problem of large stock dividends phenomenon implemented by listed companies,this paper proposes alightGBM based on Differential Evolution algorithm hyperparametric optimization(Named as DE-lightGBM).The model mainly includes two aspects:Firstly,Differential Evolution algorithm is used to adjust the weight of a few categories and the coefficient of regular term in the loss function of lightGBM to deal with the problem of data category imbalance.Secondly,taking F1and AUC as evaluation indexes,Differential Evolution algorithm is used to optimize the important hyperparametric variables of lightGBM model again to find agroup of parameter combinations with the best prediction effect.The numerical results show that the DE-lightGBM has achieved good results,and the F1and AUC are 0.5368and 0.8734respectively.DE-lightGBM proposed in this paper can effectively identify the listed companies that will implement stock dividends next year.