项目融资动态担保模型研究
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摘要
项目融资作为一种新的融资方式,有效地解决了各国经济发展过程中资金不足的问题,越来越受到各国的重视。近年来,我国一些大型基础设施项目陆续采用项目融资方式进行建设,并已取得了一定成效,项目融资在我国具有巨大的发展潜力。但从总体看,我国项目融资发展和应用的时间较短,仍是一个正在开拓的领域。特别是贷款银行作为项目融资的重要参与者之一,对于贷款时间长、资金巨大的项目贷款缺乏有效担保手段,如果项目现金流出现问题,贷款银行将蒙受损失。为解决贷款银行在项目融资中遇到的风险问题,更好地发挥贷款银行在项目融资中的促进作用,研究并建立项目融资动态担保模型,有效保障贷款银行的资金安全具有重要的理论意义和现实意义。
本研究以建立项目融资动态担保模型为研究目标,提出三个关键问题,包括银行在项目融资中面临的关键风险识别问题,项目融资动态担保模型的建立问题和银行担保金调整方法的设计问题。论文的主要研究成果如下:
首先,识别出银行在项目融资中面临的关键风险。针对现有文献中对项目融资风险论述比较系统,但尚未有从银行角度研究银行在项目融资中面临的风险,通过设计调查问卷,统计分析数据,并使用结构方程模型,完成了银行在项目融资中面临关键风险的识别并进行了检验。结果表明贷款与股本的比例、项目投资回报率对项目融资担保金的影响程度最大,属于一级风险;项目投资总额影响程度较大,属于二级风险:借款人的信誉、政府的信誉、法律的健全程度、环境污染罚款或赔偿数的影响程度最低,属于三级风险,在项目融资动态担保模型中可以不予考虑。
其次,构建了项目融资动态担保模型。针对识别出的关键风险,选取某银行2005年-2007年基础建设贷款中损失类数据,使用MATLAB软件分别拟合出单一关键风险与银行损失以及同时考虑三个关键风险与银行损失的关系模型并进行了检验。在项目融资中,银行根据预期损失收取相应的担保金,关系模型中银行损失即为担保金数量,因此将银行损失替换为银行担保金,建立了项目融资中关键风险与银行担保金之间的关系模型。由此,本研究建立了三个单风险的项目融资动态担保模型和一个多风险的项目融资动态担保模型。
再次,确定了银行担保金的调整方法。明确银行担保金调整所依据的关键风险,提出项目融资中银行担保金调整所遵循的四个原则:综合考虑风险影响的原则、激励效率提高的原则、保证合理回报的原则、分阶段调整的原则。研究认为项目融资中银行担保金调整的周期应该与项目融资三个发展阶段即建设开发阶段、项目试生产阶段、项目生产经营阶段相对应,并要考虑法律和金融监管部门对担保金数量限制的影响。
最后,利用某污水处理厂项目融资数据进行应用分析。通过提取该项目融资的投资总额、贷款与股本的比例和投资回报率等银行面临的三个关键风险的实际数据,将数据代入项目融资动态担保模型,继续使用MATLAB软件作为数据应用分析的工具,计算得出三个关键风险的单风险担保金数量和同时考虑三个关键风险的多风险担保金数量。模型应用的结果表明,本研究所建立的项目融资动态担保模型和调整方法,能够在风险识别的基础上,根据关键风险确定出银行在项目融资中应当收取的担保金数量,并依据关键风险的变化调整担保金。
As a financing method, project finance successfully solves the fund shortage problem in economic development and gains more and more recognition world-wide. In recent years, project finance has been adopted to construct some large-sale infrastructure projects, the results turn out to be effective, therefore project finance has great market potential in our country. But in general sense, project finance is still in the pioneering stage due to short time development and application. Especially for the important participator of project finance, the loan bank has no effective self-protection methods when operating long-term, large-amount loan, and will easily suffer great loss if project cash flow problem occurs. In order to solve the high risk problems for the loan bank and make full advantage of project finance, a dynamic guarantee model for project finance should be established and researched, which has both academic and realistic significance for fund safety of loan bank.
Our research aims at establishing a dynamic guarantee model for project finance, bring out three key issues, including the risk identification problem which the loan bank faces concerning project finance; how to establish the dynamic guarantee model for project finance; how to design a scientific method to adjust bank guarantee deposit. The main research results of our paper are as follows:
Firstly, identify the risks which the loan bank faces concerning project finance. Though current research works have stated clearly the risks of project finance, they are not analyzing the risks from the loan bank's angle. First design inquiry questionnaire, sorting data, and then evaluate the data with structure equation model, and finally identify the different categories of project finance risks. The result shows: first category risks are the effects of capital percentage and project investment returning rate; second category risk is the effect of total investment amount; the third category risks, whose effects are small and could be ignored in dynamic guarantee model analysis, include the borrower's credit, the government credit, the wholeness of law enforcement, environment pollution and fine, and so on.
Secondly, establish the dynamic guarantee model for project finance. We choose the infrastructure loan loss data of a certain bank from year 2005 to 2007, to simulate respectively the relation models of one multi key risk with bank loss and three single key risks with bank loss by using the MATLAB software. Then calculate the amount of guarantee deposit according to the anticipated bank loss, in this relation model bank loss equals guarantee deposit, by this way we establish the relation model between key risks and bank guarantee deposit in project finance. So our research establishes three single risks dynamic guarantee model and one multi-risk dynamic guarantee model.
Thirdly, design a scientific method to adjust bank guarantee deposit. Decide the four principles concerning bank deposit adjustment in project finance: risk effect principle; efficiency stimulation principle; reasonable return principle; step by step adjustment principle. Our research shows the bank deposit adjustment period should be correspondent to different stages of project like construction period, trial-production period and normal production period, with additional consideration of law and finance inspection department restriction on deposit amount.
Finally, we analyze the project financing data of a certain sewage disposal factory in Jiangsu Province. By picking out the project total investment amount, loan amount, capital percentage and investment return rate as three key risks, inserting the above figures into the Dynamic guarantee model, using MATLAB software as data analysis instrument, calculate respectively one multi-risk deposit amount and three single risks deposit amount. The result of data analysis shows the dynamic guarantee model established in this paper can effectively decide the scientific deposit amount during project financing process on the basis of risk identification and can adjust the deposit amount according to the changes of key risks. In real practice, the multi-risk dynamic guarantee model is more suitable for the loan bank.
本研究以建立项目融资动态担保模型为研究目标,提出三个关键问题,包括银行在项目融资中面临的关键风险识别问题,项目融资动态担保模型的建立问题和银行担保金调整方法的设计问题。论文的主要研究成果如下:
首先,识别出银行在项目融资中面临的关键风险。针对现有文献中对项目融资风险论述比较系统,但尚未有从银行角度研究银行在项目融资中面临的风险,通过设计调查问卷,统计分析数据,并使用结构方程模型,完成了银行在项目融资中面临关键风险的识别并进行了检验。结果表明贷款与股本的比例、项目投资回报率对项目融资担保金的影响程度最大,属于一级风险;项目投资总额影响程度较大,属于二级风险:借款人的信誉、政府的信誉、法律的健全程度、环境污染罚款或赔偿数的影响程度最低,属于三级风险,在项目融资动态担保模型中可以不予考虑。
其次,构建了项目融资动态担保模型。针对识别出的关键风险,选取某银行2005年-2007年基础建设贷款中损失类数据,使用MATLAB软件分别拟合出单一关键风险与银行损失以及同时考虑三个关键风险与银行损失的关系模型并进行了检验。在项目融资中,银行根据预期损失收取相应的担保金,关系模型中银行损失即为担保金数量,因此将银行损失替换为银行担保金,建立了项目融资中关键风险与银行担保金之间的关系模型。由此,本研究建立了三个单风险的项目融资动态担保模型和一个多风险的项目融资动态担保模型。
再次,确定了银行担保金的调整方法。明确银行担保金调整所依据的关键风险,提出项目融资中银行担保金调整所遵循的四个原则:综合考虑风险影响的原则、激励效率提高的原则、保证合理回报的原则、分阶段调整的原则。研究认为项目融资中银行担保金调整的周期应该与项目融资三个发展阶段即建设开发阶段、项目试生产阶段、项目生产经营阶段相对应,并要考虑法律和金融监管部门对担保金数量限制的影响。
最后,利用某污水处理厂项目融资数据进行应用分析。通过提取该项目融资的投资总额、贷款与股本的比例和投资回报率等银行面临的三个关键风险的实际数据,将数据代入项目融资动态担保模型,继续使用MATLAB软件作为数据应用分析的工具,计算得出三个关键风险的单风险担保金数量和同时考虑三个关键风险的多风险担保金数量。模型应用的结果表明,本研究所建立的项目融资动态担保模型和调整方法,能够在风险识别的基础上,根据关键风险确定出银行在项目融资中应当收取的担保金数量,并依据关键风险的变化调整担保金。
As a financing method, project finance successfully solves the fund shortage problem in economic development and gains more and more recognition world-wide. In recent years, project finance has been adopted to construct some large-sale infrastructure projects, the results turn out to be effective, therefore project finance has great market potential in our country. But in general sense, project finance is still in the pioneering stage due to short time development and application. Especially for the important participator of project finance, the loan bank has no effective self-protection methods when operating long-term, large-amount loan, and will easily suffer great loss if project cash flow problem occurs. In order to solve the high risk problems for the loan bank and make full advantage of project finance, a dynamic guarantee model for project finance should be established and researched, which has both academic and realistic significance for fund safety of loan bank.
Our research aims at establishing a dynamic guarantee model for project finance, bring out three key issues, including the risk identification problem which the loan bank faces concerning project finance; how to establish the dynamic guarantee model for project finance; how to design a scientific method to adjust bank guarantee deposit. The main research results of our paper are as follows:
Firstly, identify the risks which the loan bank faces concerning project finance. Though current research works have stated clearly the risks of project finance, they are not analyzing the risks from the loan bank's angle. First design inquiry questionnaire, sorting data, and then evaluate the data with structure equation model, and finally identify the different categories of project finance risks. The result shows: first category risks are the effects of capital percentage and project investment returning rate; second category risk is the effect of total investment amount; the third category risks, whose effects are small and could be ignored in dynamic guarantee model analysis, include the borrower's credit, the government credit, the wholeness of law enforcement, environment pollution and fine, and so on.
Secondly, establish the dynamic guarantee model for project finance. We choose the infrastructure loan loss data of a certain bank from year 2005 to 2007, to simulate respectively the relation models of one multi key risk with bank loss and three single key risks with bank loss by using the MATLAB software. Then calculate the amount of guarantee deposit according to the anticipated bank loss, in this relation model bank loss equals guarantee deposit, by this way we establish the relation model between key risks and bank guarantee deposit in project finance. So our research establishes three single risks dynamic guarantee model and one multi-risk dynamic guarantee model.
Thirdly, design a scientific method to adjust bank guarantee deposit. Decide the four principles concerning bank deposit adjustment in project finance: risk effect principle; efficiency stimulation principle; reasonable return principle; step by step adjustment principle. Our research shows the bank deposit adjustment period should be correspondent to different stages of project like construction period, trial-production period and normal production period, with additional consideration of law and finance inspection department restriction on deposit amount.
Finally, we analyze the project financing data of a certain sewage disposal factory in Jiangsu Province. By picking out the project total investment amount, loan amount, capital percentage and investment return rate as three key risks, inserting the above figures into the Dynamic guarantee model, using MATLAB software as data analysis instrument, calculate respectively one multi-risk deposit amount and three single risks deposit amount. The result of data analysis shows the dynamic guarantee model established in this paper can effectively decide the scientific deposit amount during project financing process on the basis of risk identification and can adjust the deposit amount according to the changes of key risks. In real practice, the multi-risk dynamic guarantee model is more suitable for the loan bank.
引文
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