摘要
针对科创板拟上市企业估值问题,基于所收集到的相关数据,综合运用灰色关联度、层次分析法、BP算法,构建出了灰色关联度及BP神经网络预测等模型,并运用MATLAB、SPSS进行处理分析。通过对近几年中国A股市场、美国NASDAQ市场进行对比分析,找出了中美市场估值指标与基本面指标、流动性指标之间的关系,并对2019年两市场估值指标给出了预测。通过进一步研究分析,展望了科创板的发展前景,并预测出我国首批科创板企业上市后的估值水平。
Aiming at the valuation problem of the listed companies of Kechuang board,based on the relevant data collected,the grey relational degree model and BP neural network prediction model are constructed by using grey relational degree,analytic hierarchy process and BP algorithm,and processed and analyzed by using MATLAB,Excel and SPSS.By comparing and analyzing the A-share market in China and NASDAQ market in the United States in recent years,this paper finds out the relationship between valuation indicators and basic indicators and liquidity indicators in China and the United States,and forecasts the valuation indicators of the two markets in 2019.Through further research and analysis,the prospects for the development of KSB are forecasted,and the valua level of the first batch of KSB enterprises in China after listing is predicted.
作者
朱家明
马晓旭
陈荣燕
张梦凡
ZHU Jia-ming;MA Xiao-xu;CHEN Rong-yan;ZHANG Meng-fan(School of Statistics and Applied Mathematics,Anhui University of Finance and Economics,Anhui Bengbu 233030,China;School of Finance,Anhui University of Finance and Economics,Anhui Bengbu 233030,China)
出处
《齐齐哈尔大学学报（自然科学版）》
2020年第5期79-83,94,共6页
Journal of Qiqihar University(Natural Science Edition)
基金
国家自然科学基金重点项目(71934001)
省级教研项目“大数据背景下学科竞赛对新经管人才创新能力培养研究”(2018jyxm1305)。
关键词
科创板
上市企业估值
BP神经网络
灰色关联度分析
MATLAB
Kechuang board
valuation of listed enterprises
BP neural network
grey relational degree analysis
MATLAB
