任务书
会计学
基于Logistic模型的上市公司风险预警研究
【毕论】
【业文】
( 届)砥平里
法兰西战役基于Logistic模型的上市公司风险预警研究
摘要
狼人杀怎么发言
随着国际金融市场的发展，多元化的金融工具和衍生工具在资本市场中得以运用和发展。上市公司作龙年祝福语
为自主经营、自负盈亏、自我发展的市场主体，面临着日益多变的市场环境，随时都要经受财务危机的考验。财务风险预警研究有助于对企业财务风险进行预测，动态了解企业发展的现状和未来的趋势，及时发现和解决企业财务管理中存在的问题，降低发生财务危机的概率，具有重大的现实意义。
本次研究选取我国深沪两市共70家上市公司（均为制造行业）2007年的财务报表数据，通过因子分析降维，将16个财务指标浓缩为4个主成分因子，将4个主成分因子作为自变量建立回归模型。从制造行业上市公司的财务状况的盈利能力、偿债能力、发展能力和营运能力角度，揭示财务指标在企业发展中所起的信号作用。在选取变量、建立模型后，得到的整体预测水平较高，模型效果良好，可以将该模型运用于我国上市公司的制造行业，为其提供财务风险防范方面的帮助。
关键词：财务指标；财务风险预警；因子分析；Logistic模型我和嫂子的故事>跑步后的拉伸运动
Abstract
With the development of international financial markets,a wide range of financial instruments and derivatives are Applied and Developed, in the capital market. Listed Companies as autonomous, lf-financing, lf-development of the market players, is facing an increasingly volatile market environment, always have to stand the test of the financial crisis. Financial Risk rearch can help predict the risk of corporate finance, business development dynamic understanding of the status and
梦见打狗
日式烤鳗鱼future trends, to discover and solve business problems in financial management and reduce the probability of financial distress, is of great practical significance.
The study lected 70 cities of Shanghai and Shenzhen listed companies (both manufacturing industry) in 2007 financial statement data, dimensionality reduction through factor analysis, the concentration of 16 financial indicators for the four principal components, the four main Component factor regression model as independent variables. Listed manufacturing companies from the financial position of profitability, solvency, capacity development and operational capabilities point of view, reveals the development of financial indicators in the business played a signal role. In lecting variables, model building, the resulting high level of overall forecast, the model works well, the model can be applied to listed companies in China's manufacturing industry, providing help with financial risk.
Keywords: Financial Indicators ;Warning of financial risk ; Factor Analysis;Logistic model
