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机构地区:[1]上海理工大学管理学院,上海200093 [2]石家庄经济学院,河北石家庄050031
出 处:《技术经济与管理研究》2011年第1期7-10,共4页Journal of Technical Economics & Management
基 金:国家自然科学基金项目(70871080);教育部博士点基金项目(20070252002);上海市重点学科项目(S30504)
摘 要:对所有2008年在上海证券交易所的上市公司按照总市值、营业收入和净利润排名,得到前100名和后100名的上市公司,然后随机地抽取100名上市公司。用向前逐步筛选法在13个综合能力指标中选取了每股净资产、净资产收益率、总资产周转率和净资产比率四个变量。建立了以后100名上市公司、前100名的上市公司和随机地抽取的100名为分类因变量,这四个变量为自变量的上市公司的两个标准化系数和两个非标转化系数的判别分类函数以及Fisher判别函数,原始回代法验证了判别函数对上市公司的分类准确率达到58.85%,交互印证法验证了判别函数对上市公司的分类准确率达到57.2%。All listed companies in the Shanghai Stock Exchange in 2008 were ranked according to the total market capitalization, the revenue and the net profit. The top 100 listed companies and the countdown listed companies were selected. Then the random 100 listed companies were extracted. The two standardized coefficient discrimination classification functions and the two non-standardized coefficient discrimination classification functions and Fisher discrimination functions of the listed companies in accordance with the comprehensive ability indexes were established by the three types companies as categorical dependent variables and the net assets per share, the return on equity, the total assets turnover and he net assets ratio as the independent variables that were selected among the 13 comprehensive ability indexes by the forward stepwise method. The accuracy rate of the discrimination classification functions of the listed companies is 58.85% through verifying by the original back substitution. The accuracy rate of the discrimination classification functions of the listed companies is 57.2% through verifying by interactive proof method.
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