Abstract：For companies listed on the Shenzhen Stock Exchange,by analyzing and mining the data in their quarterly reports or related transaction websites,extracting the relevant data characteristics from the ranking prediction task and the text characteristics obtained through the crawler,successfully constructed the company's share-earnings model.The model can achieves a reasonable prediction of the ranking of valuation gains.The experimental results show that our proposed model can effectively improve the performance of stock price ranking prediction tasks,and the SPRP-Random Forests model can reach 0.9583 in the NDCG@10 evaluation index.In the selection of stocks for investors,the company's business model adjustment and other aspects have certain practical value.
孙伯维,姚念民,孙玉轩. 面向排名预测的上市公司股价收益研究[J]. 小型微型计算机系统, 2020, 41(1): 35-39.
SUN Bo-wei,YAO Nian-min,SUN Yu-xuan. Research on Economic Data of Listed Companies for Ranking Forecasting. Journal of Chinese Computer Systems, 2020, 41(1): 35-39.
2020, Vol. 41 
