复杂环境下我国企业财务困境模式及预警研究
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摘要
企业财务困境问题始终是企业经营和财务管理中的重要问题。企业财务困境轻则严重影响着企业的健康发展和信用机构、证券投资者的利益,重则可能危及国家的经济安全乃至引发世界性的经济危机。随着经济一体化的不断加快,企业间的竞争日趋激烈。市场的瞬变性和不可准确预见性,加之各种内外部因素,企业所面临的内外部环境的复杂性比以前极大增加。2008年,金融海啸的爆发严重阻碍了世界经济的发展,企业财务困境预警的研究受到高度重视,被提到了前所未有的高度。如何更好地理解复杂环境下企业财务困境产生的原因和过程,并有效地对复杂环境下企业财务困境进行预警已成为迫切需要解决的问题。
鉴于已有对复杂环境下企业财务困境研究的不足,对复杂环境下企业财务困境问题的研究需要开拓新的思路和方法,为此本文拟从企业生命周期和集成模型两个角度出发来研究复杂环境下的企业财务困境问题。由于企业在不同生命周期阶段面临的环境的复杂性存在差异,而且不同生命周期阶段的企业在对复杂环境的感知和应对能力上也存在显著差别,因此,企业生命周期理论为复杂环境下企业财务困境研究提供了重要的工具和新的视角。在企业财务困境预警方面,已有财务困境预警模型多以传统单分类器预测模型为主,忽略了多分类器集成在财务困境预警时的优势。由于单分类器预测绩效一定程度上取决于样本的模式特征,且各单分类器模型预测具有不确定性,其在复杂环境下是否有效和适用令人质疑。非线性融合方法Choquet模糊积分是不确定环境下一种强硬有力的推理方法,通过Choquet模糊积分对单分类器模型的集成可以实现扬长避短、信息互补的效果,为复杂环境下企业财务困境预警提供了新的办法。
在复杂环境背景下,本文从企业生命周期角度出发,在文献分析基础上,借助案例分析、仿真模拟及实证研究等手段,系统分析了复杂环境下企业财务困境的原因和过程,并在此基础上创造性地提出了复杂环境下企业不同生命周期阶段财务困境的产生模式。鉴于以往企业财务困境单分类器预测模型的片面性和不确定性,本文通过融合企业生命周期理论(Enterprise life cycle, LC)和基于Choquet积分的多分类器集成方法,探索建立一个基于企业生命周期和Choquet积分(LC-Choquet)的企业财务困境预警集成模型,以期大大提高复杂环境下企业财务困境预警模型的预测精度。
首先,提出了不同生命周期阶段企业财务困境发生模式,为复杂环境下企业财务困境研究提供了新视角。在对已有文献进行分析的基础上,结合企业不同生命周期阶段的特征,通过理论分析、案例研究和仿真模拟等方法系统提出了不同企业生命周期阶段的财务困境产生模式。即：初创期企业发生财务困境的可能性与企业年龄呈倒“U”型关系,管理者的管理经验和行业经验、初创期企业的规模以及行业和宏观环境因素等是造成初创期企业财务困境的主要原因；成长期企业容易因管理者过度自信而陷入“成长幻象”的陷阱,导致企业财务困境；成熟期企业隐含着严重的公司治理风险,一旦公司治理不善,则很有可能引发经理层的“道德风险”和大股东对公司的“掏空”,从而引发成熟期企业的财务困境；衰退期企业由于自身组织结构的老化和创新力减退,衰退期企业很有可能陷入因产品生命周期的结束而导致的企业财务困境。
其次,构建了一个基于多智能体的企业财务困境仿真模型,为理解企业财务困境发生的过程提供了新的分析工具。通过运用AnyLogic软件构建基于多智能体的企业财务困境仿真模型对企业不同生命周期阶段财务困境产生的模式进行了模拟仿真,仿真结果有力地支持了企业不同生命周期阶段具有不同财务困境模式的结论。
再次,较全面地识别出了企业不同生命周期阶段财务困境的关键因素。探讨影响企业财务困境的关键因素也是企业财务困境研究领域的重要内容之一,为了弥补现有的国内外关于财务困境关键因素的研究大多没有考虑和区分企业不同生命周期的不足,本文通过运用现金流法对企业不同生命周期阶段进行划分,并采用因子分析法和Logistic回归方法从企业财务因素和非财务因素两个层面对财务困境的关键因素进行了实证研究,识别出不同生命周期阶段企业财务困境的关键因素。实证结果表明：成长期企业财务困境的关键因素包括盈利能力、成长能力、营运能力、偿债能力、主营业务鲜明率,现金流状况和股权集中度；成熟期企业财务困境的关键因素包括盈利能力、成长能力、现金流状况和主营业务鲜明率；衰退期企业财务困境的关键因素包括营运能力、主营业务鲜明率、长期偿债能力和股权结构。对企业不同生命周期阶段财务困境关键因素的识别不仅为企业财务困境预警指标的选取提供了新的思路,也为企业根据自身所在的生命周期阶段有针对性地防范企业财务困境提供了具体指导。
然后,构建了一个基于LC-Choquet的企业财务困境预警集成模型。考虑复杂环境对企业财务困境的影响,本文在基于企业生命周期的财务困境模式基础上,提出了一种采用非线性融合方法Choquet模糊积分对财务困境单分类器进行集成的企业财务困境预警集成模型。该模型一方面考虑了企业不同生命周期阶段的特征,另一方面采用的非线性融合方法Choquet模糊积分,与以往以最大值法、平均方法和投票模型为代表的线性融合方法相比不但考虑了单个分类器的预测结果,而且考虑了各种分类器的相对重要程度以及各分类器之间的交互作用。通过采用中国上市公司数据进行实证研究,结果表明,本文提出的基于LC-Choquet的企业财务困境预警集成模型极大地提高了企业财务困境预警的准确性,从而为企业、股东、银行等利益相关者更好地提前防范复杂环境下企业可能发生的财务危机,预先采取应对措施以避免损失提供了有力支持。
最后,通过用识别条件下的动态信息对静态模糊密度进行修正,提出了更适合于复杂环境下的自适应模糊测度。模糊测度是模糊积分的关键和重点,以往研究使用混淆矩阵进行模糊测度计算时往往忽视了训练条件和识别条件的差别。本文不但考虑了训练条件下的静态模糊密度,而且利用识别条件下的动态信息从单分类器输出的信度和单分类器输出结果的一致性两方面对静态模糊密度进行了修正,提出了更适合复杂环境下的自适应模糊测度,从而为基于Choquet积分企业财务困境预警集成模型提供了基础。
针对企业不同生命周期阶段财务困境产生模式,本文针对性地提出了相关对策建议,以用于指导各生命周期阶段的企业避免风险、误入陷阱和歧途,从而为企业及债权人、股东等利益相关者避免损失,维持社会经济秩序的稳定和国家的经济安全提供重要参考。
The problem of corporate financial distress has received much attention in the field of business and financial management in the past decades. It has serious adversary effect on which ranges from healthy development of enterprises, to the interests of credit institutions and secruities investors, envn to the economic security of countries which might trigger a worldwide economic crisis. The continous acceleration of business globalization and fiece competition among the companies around the world increase the uncertainty and unpredictability of the market, which makes enterprises face a far more complex internal and external economic enviroment than before. The global financial crisis, started from 2008, has seriously hindered the pace of the development of world economy, which lifts the importance of early warning of corporate financial crisis to an unprecedented high position. Therefore, it is urgent to understant the causes and process of formation mechinism of corporate financial distress under complex enviroment for better and precise early warning of corporate fiancial distress.
The previous studies don't provide sufficient implications on corporate financial distress under the complex environment. Thus some new ideas and methods must be developed for it. Consequently this article focuses on this problem from two perspectives of enterprise life cycle and integration early warning models. First, enterpersie life cycle theory could provide some significant suggestions on the problem of corporate financial distress. Because there are significant differences of the enviroment the enterprises face among their different enterprise life cycle and also the enterprises in different life cycle stages have different ways and abilities to perceive and respond to their external environment. Second, pervious research on the topic of early warning models of corporate financil stress mainly use the single classfier to predicate the financial conditions of enterprises, neglecting the advantages of the integration models of mutiple classifiers. The performance of a single classifier depends on the characterisitics of samples and also is uncertain because different classfiers might have different results of prediction, which makes its validity questionable. Therefore, this article employs Choquet fuzzy integral method, which is a tough powerful nonlinear reasoning method for uncertain environment, to integrate different single classifiers. This method could take the advantages of single classfiers together and make the information of different classifiers complementary, providing a great tool for early warning of corporate financial distress under complex environment.
In the context of complex environments, from the perspective of corporate life cycle, based on the previous literatures, using case studies, simulation and empirical research methods, this article systematicly anaylizes the causes and formation processes of corporate financial distress and innovatively bring forward the formation models for corporates in different life cycle stages. Meanwhile, in view of the uncertainty of previous financial distress prediction model, this paper combines enterprise life cycle theory and Choquet fuzzy integral method to explore a new integration early warning model of corporate finanical distress under complex environment in order to greatly enhance the prediction accuracy.
First, this article puts forward formation models of corporate financial distress generated in different life cycle stages, on the basis of analyzing the literature, combining with the characteristics of enterprises in different life cycle stages, through theoretical analysis, case studies and simulation methods, which also provides a new perspective for the study of corporate financial distress under complex environment. For start-up companies, there is an inverted "U" shaped relationship between the possibility that financial distress happens to a start-up company and the company age. The mainly factors that cause a start-up company into financial distress are manager's experience on business mangement and industries, the enterprises'scale and marcoeconomic enivironment. Growing companies who expand extremely fast because of the over confidence of managers often easily go through financial distress. For mature companies, a poor corporate governnance might trigger the "moral hazard" of managers and leads major shareholders tunelling the money out from the company, which easily causes corporate financial distress. For the companies in the recession stage, due to the poor flexiability of organization and poor ability of innovation, the companies might go into the end of product life cycle and finaical distress.
Second, this article establishes a model based on mutilple intelligent agents for simulating the process of corporate financial distress formation, which provides a new tool for anaylizing corporate fianncial distress. With the Anylogic software we simualte the process how corporates in different life cycle stages get financial distress. The simualtion results strongly support the models we have put forward.
Third, this article comprehensively identifies the key factors that make corporates in different life cycle stages get financial distress, which also is one of the important research fields of corporate financial distress. The previous study neglected the factor of enterprise life cycle. Therefore, this article uses cash flow method identifying which life cycle stage a corporate is going through, then identifies key factors of different life cycle stages from two aspects of financial factors and non-financial factors with the method of factor analysis and logistic regression. The results show that for growing companies, the key factors includes profitability, growth capacity, operational capacity, solvency, main business concentraion, cash flow status and ownership concentration; for mature companies, the key factors include profitability, growth capacity,, and cash flow status and main business concentraion; for companies in recession stage, the key factors include operational capacity, main business concentraion, long-term solvency, equity structure. Identifying the key factors of different enterprise life cycle that cause financial distress not only gives some suggestions for the selection of indicators of early warning models, but also provides implications for enterprises to adjust their situation according to the life cyle they are in.
Fourth, this article establishes an integration model for predicting financial distress based on the combination of life cycle theory and Choquet fuzzy integral, considering the impact of complex environment on enterprieses. On the one hand, this model takes the different charecterisetics of enterprises in different life cycle stages into account. On the other hand, this model employs the nonlinear Choquet fuzzy integral method, which not only focuses on the prediction results of single classifier but also consider the comprative weight and interaction effect of different classifiers, compared to linear methods represented by maximum method, average method and vote model. Then this article takes the data sample of Chinese listed companies for empirical study. The results show that the early warning model we establish greatly improve the accuracy of predicting corporate financial distress, which could help stakeholders prevent the occurrence of financil distress by taking some mearsures in advance to avoid the loss of interests.
Finally, this article proposes an adatptive fuzzey mearsure for complex environment by adjusting static fuzzy density with the dynamic information under identifying condition. Fuzzy measures are the key part of fuzzy integral. The previous studies which use the confusion matrix for fuzzy measures often overlook the differences between training condition and identifying condition. This article not only takes the static fuzzy density under training condition into account, but also adjusts the static fuzzy density from the aspects of the validity results the output results of single classifiers by using the dynamic information under the identifying condition, which lays the foundation of Choquet fuzzy integral for the early warning models of corporate financial distress under complex environment.
Having understanded the formation mechnism of financial distress generated in corporates'different life cycle stages, this article correspondingly brings forward some suggetstions to help enterprises of all life cycles avoid the risk of financial distress and help stakeholders such as shareholders, debt owners avoid the economic loss, which has great implictions for a stable eocomic order of socities and the ecocnomic security of countries.
鉴于已有对复杂环境下企业财务困境研究的不足,对复杂环境下企业财务困境问题的研究需要开拓新的思路和方法,为此本文拟从企业生命周期和集成模型两个角度出发来研究复杂环境下的企业财务困境问题。由于企业在不同生命周期阶段面临的环境的复杂性存在差异,而且不同生命周期阶段的企业在对复杂环境的感知和应对能力上也存在显著差别,因此,企业生命周期理论为复杂环境下企业财务困境研究提供了重要的工具和新的视角。在企业财务困境预警方面,已有财务困境预警模型多以传统单分类器预测模型为主,忽略了多分类器集成在财务困境预警时的优势。由于单分类器预测绩效一定程度上取决于样本的模式特征,且各单分类器模型预测具有不确定性,其在复杂环境下是否有效和适用令人质疑。非线性融合方法Choquet模糊积分是不确定环境下一种强硬有力的推理方法,通过Choquet模糊积分对单分类器模型的集成可以实现扬长避短、信息互补的效果,为复杂环境下企业财务困境预警提供了新的办法。
在复杂环境背景下,本文从企业生命周期角度出发,在文献分析基础上,借助案例分析、仿真模拟及实证研究等手段,系统分析了复杂环境下企业财务困境的原因和过程,并在此基础上创造性地提出了复杂环境下企业不同生命周期阶段财务困境的产生模式。鉴于以往企业财务困境单分类器预测模型的片面性和不确定性,本文通过融合企业生命周期理论(Enterprise life cycle, LC)和基于Choquet积分的多分类器集成方法,探索建立一个基于企业生命周期和Choquet积分(LC-Choquet)的企业财务困境预警集成模型,以期大大提高复杂环境下企业财务困境预警模型的预测精度。
首先,提出了不同生命周期阶段企业财务困境发生模式,为复杂环境下企业财务困境研究提供了新视角。在对已有文献进行分析的基础上,结合企业不同生命周期阶段的特征,通过理论分析、案例研究和仿真模拟等方法系统提出了不同企业生命周期阶段的财务困境产生模式。即：初创期企业发生财务困境的可能性与企业年龄呈倒“U”型关系,管理者的管理经验和行业经验、初创期企业的规模以及行业和宏观环境因素等是造成初创期企业财务困境的主要原因；成长期企业容易因管理者过度自信而陷入“成长幻象”的陷阱,导致企业财务困境；成熟期企业隐含着严重的公司治理风险,一旦公司治理不善,则很有可能引发经理层的“道德风险”和大股东对公司的“掏空”,从而引发成熟期企业的财务困境；衰退期企业由于自身组织结构的老化和创新力减退,衰退期企业很有可能陷入因产品生命周期的结束而导致的企业财务困境。
其次,构建了一个基于多智能体的企业财务困境仿真模型,为理解企业财务困境发生的过程提供了新的分析工具。通过运用AnyLogic软件构建基于多智能体的企业财务困境仿真模型对企业不同生命周期阶段财务困境产生的模式进行了模拟仿真,仿真结果有力地支持了企业不同生命周期阶段具有不同财务困境模式的结论。
再次,较全面地识别出了企业不同生命周期阶段财务困境的关键因素。探讨影响企业财务困境的关键因素也是企业财务困境研究领域的重要内容之一,为了弥补现有的国内外关于财务困境关键因素的研究大多没有考虑和区分企业不同生命周期的不足,本文通过运用现金流法对企业不同生命周期阶段进行划分,并采用因子分析法和Logistic回归方法从企业财务因素和非财务因素两个层面对财务困境的关键因素进行了实证研究,识别出不同生命周期阶段企业财务困境的关键因素。实证结果表明：成长期企业财务困境的关键因素包括盈利能力、成长能力、营运能力、偿债能力、主营业务鲜明率,现金流状况和股权集中度；成熟期企业财务困境的关键因素包括盈利能力、成长能力、现金流状况和主营业务鲜明率；衰退期企业财务困境的关键因素包括营运能力、主营业务鲜明率、长期偿债能力和股权结构。对企业不同生命周期阶段财务困境关键因素的识别不仅为企业财务困境预警指标的选取提供了新的思路,也为企业根据自身所在的生命周期阶段有针对性地防范企业财务困境提供了具体指导。
然后,构建了一个基于LC-Choquet的企业财务困境预警集成模型。考虑复杂环境对企业财务困境的影响,本文在基于企业生命周期的财务困境模式基础上,提出了一种采用非线性融合方法Choquet模糊积分对财务困境单分类器进行集成的企业财务困境预警集成模型。该模型一方面考虑了企业不同生命周期阶段的特征,另一方面采用的非线性融合方法Choquet模糊积分,与以往以最大值法、平均方法和投票模型为代表的线性融合方法相比不但考虑了单个分类器的预测结果,而且考虑了各种分类器的相对重要程度以及各分类器之间的交互作用。通过采用中国上市公司数据进行实证研究,结果表明,本文提出的基于LC-Choquet的企业财务困境预警集成模型极大地提高了企业财务困境预警的准确性,从而为企业、股东、银行等利益相关者更好地提前防范复杂环境下企业可能发生的财务危机,预先采取应对措施以避免损失提供了有力支持。
最后,通过用识别条件下的动态信息对静态模糊密度进行修正,提出了更适合于复杂环境下的自适应模糊测度。模糊测度是模糊积分的关键和重点,以往研究使用混淆矩阵进行模糊测度计算时往往忽视了训练条件和识别条件的差别。本文不但考虑了训练条件下的静态模糊密度,而且利用识别条件下的动态信息从单分类器输出的信度和单分类器输出结果的一致性两方面对静态模糊密度进行了修正,提出了更适合复杂环境下的自适应模糊测度,从而为基于Choquet积分企业财务困境预警集成模型提供了基础。
针对企业不同生命周期阶段财务困境产生模式,本文针对性地提出了相关对策建议,以用于指导各生命周期阶段的企业避免风险、误入陷阱和歧途,从而为企业及债权人、股东等利益相关者避免损失,维持社会经济秩序的稳定和国家的经济安全提供重要参考。
The problem of corporate financial distress has received much attention in the field of business and financial management in the past decades. It has serious adversary effect on which ranges from healthy development of enterprises, to the interests of credit institutions and secruities investors, envn to the economic security of countries which might trigger a worldwide economic crisis. The continous acceleration of business globalization and fiece competition among the companies around the world increase the uncertainty and unpredictability of the market, which makes enterprises face a far more complex internal and external economic enviroment than before. The global financial crisis, started from 2008, has seriously hindered the pace of the development of world economy, which lifts the importance of early warning of corporate financial crisis to an unprecedented high position. Therefore, it is urgent to understant the causes and process of formation mechinism of corporate financial distress under complex enviroment for better and precise early warning of corporate fiancial distress.
The previous studies don't provide sufficient implications on corporate financial distress under the complex environment. Thus some new ideas and methods must be developed for it. Consequently this article focuses on this problem from two perspectives of enterprise life cycle and integration early warning models. First, enterpersie life cycle theory could provide some significant suggestions on the problem of corporate financial distress. Because there are significant differences of the enviroment the enterprises face among their different enterprise life cycle and also the enterprises in different life cycle stages have different ways and abilities to perceive and respond to their external environment. Second, pervious research on the topic of early warning models of corporate financil stress mainly use the single classfier to predicate the financial conditions of enterprises, neglecting the advantages of the integration models of mutiple classifiers. The performance of a single classifier depends on the characterisitics of samples and also is uncertain because different classfiers might have different results of prediction, which makes its validity questionable. Therefore, this article employs Choquet fuzzy integral method, which is a tough powerful nonlinear reasoning method for uncertain environment, to integrate different single classifiers. This method could take the advantages of single classfiers together and make the information of different classifiers complementary, providing a great tool for early warning of corporate financial distress under complex environment.
In the context of complex environments, from the perspective of corporate life cycle, based on the previous literatures, using case studies, simulation and empirical research methods, this article systematicly anaylizes the causes and formation processes of corporate financial distress and innovatively bring forward the formation models for corporates in different life cycle stages. Meanwhile, in view of the uncertainty of previous financial distress prediction model, this paper combines enterprise life cycle theory and Choquet fuzzy integral method to explore a new integration early warning model of corporate finanical distress under complex environment in order to greatly enhance the prediction accuracy.
First, this article puts forward formation models of corporate financial distress generated in different life cycle stages, on the basis of analyzing the literature, combining with the characteristics of enterprises in different life cycle stages, through theoretical analysis, case studies and simulation methods, which also provides a new perspective for the study of corporate financial distress under complex environment. For start-up companies, there is an inverted "U" shaped relationship between the possibility that financial distress happens to a start-up company and the company age. The mainly factors that cause a start-up company into financial distress are manager's experience on business mangement and industries, the enterprises'scale and marcoeconomic enivironment. Growing companies who expand extremely fast because of the over confidence of managers often easily go through financial distress. For mature companies, a poor corporate governnance might trigger the "moral hazard" of managers and leads major shareholders tunelling the money out from the company, which easily causes corporate financial distress. For the companies in the recession stage, due to the poor flexiability of organization and poor ability of innovation, the companies might go into the end of product life cycle and finaical distress.
Second, this article establishes a model based on mutilple intelligent agents for simulating the process of corporate financial distress formation, which provides a new tool for anaylizing corporate fianncial distress. With the Anylogic software we simualte the process how corporates in different life cycle stages get financial distress. The simualtion results strongly support the models we have put forward.
Third, this article comprehensively identifies the key factors that make corporates in different life cycle stages get financial distress, which also is one of the important research fields of corporate financial distress. The previous study neglected the factor of enterprise life cycle. Therefore, this article uses cash flow method identifying which life cycle stage a corporate is going through, then identifies key factors of different life cycle stages from two aspects of financial factors and non-financial factors with the method of factor analysis and logistic regression. The results show that for growing companies, the key factors includes profitability, growth capacity, operational capacity, solvency, main business concentraion, cash flow status and ownership concentration; for mature companies, the key factors include profitability, growth capacity,, and cash flow status and main business concentraion; for companies in recession stage, the key factors include operational capacity, main business concentraion, long-term solvency, equity structure. Identifying the key factors of different enterprise life cycle that cause financial distress not only gives some suggestions for the selection of indicators of early warning models, but also provides implications for enterprises to adjust their situation according to the life cyle they are in.
Fourth, this article establishes an integration model for predicting financial distress based on the combination of life cycle theory and Choquet fuzzy integral, considering the impact of complex environment on enterprieses. On the one hand, this model takes the different charecterisetics of enterprises in different life cycle stages into account. On the other hand, this model employs the nonlinear Choquet fuzzy integral method, which not only focuses on the prediction results of single classifier but also consider the comprative weight and interaction effect of different classifiers, compared to linear methods represented by maximum method, average method and vote model. Then this article takes the data sample of Chinese listed companies for empirical study. The results show that the early warning model we establish greatly improve the accuracy of predicting corporate financial distress, which could help stakeholders prevent the occurrence of financil distress by taking some mearsures in advance to avoid the loss of interests.
Finally, this article proposes an adatptive fuzzey mearsure for complex environment by adjusting static fuzzy density with the dynamic information under identifying condition. Fuzzy measures are the key part of fuzzy integral. The previous studies which use the confusion matrix for fuzzy measures often overlook the differences between training condition and identifying condition. This article not only takes the static fuzzy density under training condition into account, but also adjusts the static fuzzy density from the aspects of the validity results the output results of single classifiers by using the dynamic information under the identifying condition, which lays the foundation of Choquet fuzzy integral for the early warning models of corporate financial distress under complex environment.
Having understanded the formation mechnism of financial distress generated in corporates'different life cycle stages, this article correspondingly brings forward some suggetstions to help enterprises of all life cycles avoid the risk of financial distress and help stakeholders such as shareholders, debt owners avoid the economic loss, which has great implictions for a stable eocomic order of socities and the ecocnomic security of countries.
引文
1本论文得到了国家自然科学基金青年基金项目,“复杂环境下我国企业财务困境形成机制及预警研究——基于企业生命周期的视角”(编号：71001108),2011-2013年。
肖艳.上市公司“掏空”现象透视：以ST猴王为例[J].当代经济,2004,(10).
6我们的模型参考了由XJ Technologies公司所开发的AnyLogic中的Demo, Product Portfolio Management模型。
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