【作者】 李志强；

【导师】 史本山；

【作者基本信息】 西南交通大学 ， 企业管理， 2009， 博士

【摘要】 证券市场是一个充满信息的市场,充分可靠的信息披露是证券市场有效运行的基础。会计信息披露又是证券市场信息披露的重要内容,投资者可以利用公开披露的信息对上市公司的财务状况、经营成果及未来成长性进行分析,评价证券的投资价值,做出合理的投资决策。上市公司财务信息披露的内容对投资者的投资决策影响作用是举足轻重的。然而投资者在解读上市公司的财务信息时,由于阅读技能或是出于搜索成本的考虑等原因,却可能面临两方面的风险。一是未能正确识别财务失败的风险,是从财务报告所反映的上市公司的质量方面来说的。二是不能有效识别财务失真的风险,是从财务报告的真实性和可靠性这个角度而言的。对这两方面的风险加以预警分析从而有效控制具有重要的理论和现实意义。从已有的研究文献来看,财务失败(困境)预警的研究文献较为丰富,从Altman的Z模型、Logit模型到神经网络、递归分割算法等,出现了较多的预警模型。财务失真预警的研究相对开展的较晚,文献相对较少,实证研究在国内尚处于起步阶段。两方面的研究相互脱节,缺乏必要的综合性的研究。本文研究目的在于分析投资者应对上市公司财务报告所可能面临的财务失败和财务失真风险问题,通过风险预警模型的构建为投资者等财务信息的使用者提供一个全面规避投资风险的较好方法。围绕这个目的,主要的逻辑思路是遵循理论、模型、应用这样的顺序来展开的。在对国内外相关财务失败、财务失真预警研究文献回顾和述评的基础上,提出本文所要研究的问题。从投资者应对的角度,展开基于会计信息分析的投资风险的描述。由会计信息价值的经济学解释、会计信息的相关性和可靠性的质量要求,引出财务失败和财务失真的投资风险问题,对会计信息价值的难以实现和投资风险的形成进行充分论述。在对风险由一维向二维拓展的基础上,提出基于财务失败和财务失真的双元投资风险预警问题。在投资风险预警模型研究方面,本文选取了偿债能力、现金流量能力等40个财务指标和公司治理、市场信息等23个非财务指标,共计63个维度的变量指标,并利用上市公司的相关数据,分别进行了财务失败、财务失真、双元投资风险预警等建模工作。研究发现非财务指标的引入确实有助于预警准确度的提高。针对财务失真预警传统方法预警准确度较低的问题,本文选用粗糙集结合神经网络的方法进行建模,取得了较好的效果。在财务失败、财务失真模型构建的基础上,以投资者谨慎投资的稳健性原则为前提,以出现ST或违规现象的上市公司为研究对象,尝试性地建立双元综合预警模型,并对模型的适用性和准确性进行了研究。在应用方面,本文对投资者如何分析和应对基于会计信息的二维投资风险进行了研究,根据前面的实证结论,探讨如何利用预警模型进行相应的风险分析；建立了投资者和上市公司的二维博弈模型,并给出应对投资风险的对策和建议。论文的创新性在于首次提出了基于财务失败和财务失真的双元投资风险预警分析方法。由会计信息的价值和价值难以实现所导致的投资风险问题入手,对上市公司的会计信息和投资者投资风险的关系进行了系统的一体化的研究,在对风险拓展的基础上,提出基于财务失败和财务失真的双元投资风险预警分析方法,在一定程度上拓展和丰富了财务预警基本理论；通过预警模型的系列研究,验证了上述思想并提供了具有较高理论价值和实际应用价值的预警模型,双元模型的尝试性建模突破了传统的预警建模方式；为投资者提供了一个全面系统的分析和应对风险的方法。在风险的分析方面,本文提出投资者先根据双元模型进行风险的综合判断,再根据需要利用财务失败或财务失真预警模型做进一步的常规性分析和舞弊性分析。在风险的应对方面,论文首次把多维博弈理论引入财务风险分析领域,基于多维博弈模型的建议和对策比单维模型更具针对性和现实意义。更多还原

【Abstract】 Securities market is an information market to some degree. Enough reliable information is the basis of an effective securities market. Disclosure of accounting information is one of the most important information disclosures in securities. Investors can evaluate some securities and make good investment decisions by analyzing the financial and operational condition and future growth of some listed companies according to the disclosed public financial information. It is common sense that the disclosed public financial information often leads to investors’decisions.Because of their poor reading skill or great information searching cost, investors may face two kinds of risks when they interpret financial information of listed companies. From the aspect of listed companies’quality reflected by financial reports, it is financial failure risk. From the aspect of the reports’ authenticity and reliability, it is financial distortion risk. It is very important theoretically and practically that these two kinds of risks are analyzed and effectively controlled.There are many literatures about the financial failure alarm, such as Altman’s Z model, Logit model, neural networks and recursive partitioning algorithm so on. The researches of the financial distortion early-warning are carried out relatively late. The literature is relatively fewer. Empirical research in China is still in its infancy. Two studies out of touch each other, and lack of the necessary integrated research.The purpose of this paper is to analyze the financial failure and financial distortion faced by investors when they read and interpret the financial reports of listed companies. In order to do this, this paper is organized according to the following logic order from such aspects as theory, model and application.The research background of this thesis is discussed firstly. We reviewed the theoretical research related to financial failure and financial distortion alarm at home and abroad. Based on this, the issues in this paper are proposed. From the point of view of investors, the investment risk based on the analysis of accounting information is descripted. We put forward this risk base on the analysis the relevance of accounting information quality and reliability requirements. Then we talk about the difficulty of realization of accounting information value and the formation of investment risk. The dual investment risks warning based on financial failure and financial distortion is proposed.We selected for 40 financial indicators (such as solvency, cash flow etc), and 23 non-financial indicators (such as capabilities of corporate governance, market information). For a total of 63 dimensions of indicators, three models for warning of financial failure and financial distortion and dual investment risk are built and soluted by using the new data of listed companies. We found that the introduction of non-financial indicators contribute to the improvement of the accuracy of early warning. In order to overcome the problem which accuracy of traditional methods is not high for the financial distortion alarm, we chosed model which combined rough set method with neural network for early warning, and achieved good results. Based on the results obtained in the early research, Dual investment risk warning model is built. Its applicability and accuracy is stated.Finally, we talked about how to use the theory of risk analysis. A game model including investors and listed companies is established in order to get more insight. Some countermeasures and suggestions are given.The main original results are of the following:We study the relationship between the investment risks and the information of listed companies. Mothod of dual-investment risk warning analysis based on financial failure and financial distortion is proposed. It improves theories of financial early warning. Dual-investment risk warning model is established. It verifies the above ideas and provide us with a model which riched in value of practical application. It gives investors a good method of comprehensive analysis and response. The Two-dimensional game theory is used to obtain some new insights. Some of these insights can be used by financial information user, such as investors.更多还原