近年来高送转题材受到投资者的追捧,但是对高送转股票的预测模型多采用主观性较强的打分排序法。本文深入分析了各主要因素对高送转行为的影响程度,采用Logistic回归与主成分分析相结合的方法,构建了年报高送转股票的预测模型,并用2009~2015年高送转股票样本数据对模型进行了验证。实证结果显示,模型正确率在55%以上,预测准确度最高可达80.91%。 In recent years, the subject of high-speed transfer sought after by investors, but to send more stock to send the forecast model using more subjective subjective ranking method. This paper analyzes in depth the impact of each major factor on the behavior of high delivery and delivery, and uses the combination of Logistic regression and principal component analysis to construct the forecast model of high delivery and delivery of stocks, and uses the sample of high delivery and delivery stocks from 2009 to 2015 The model was verified. The empirical results show that the accuracy of the model is above 55% and the prediction accuracy is up to 80.91%.