区域金融生态评估方法研究
|
摘要
金融生态是各类金融活动主体之间、金融活动主体与其外部金融环境之间通过相互作用、相互影响而形成的相互依赖的动态平衡系统。如何在金融危机下建设良好的金融生态体系,在危机中发现我国金融业发展的机遇,如何科学准确地对区域金融生态进行评估,已成为理论与实务界共同关注的话题。本文旨在为我国区域金融生态评估提供一种更为科学有效的方法。
本文采用比较分析方法,在对当前各种区域金融生态评估方法进行梳理比较的基础上,结合我国区域金融生态特点及区域金融生态的评估目的,对适合于我国区域金融生态评估的方法进行理论与实践上的探索。
首先,文章从金融生态理论入手,明确区域金融生态评估目的和特点,对区域金融生态概念以及区域金融生态评估进行界定。在此基础上以区域金融生态是一个复杂巨系统为前提,指出当前各种指标体系存在的问题,并从层次性角度提出区域金融生态指标体系的合理设计。
其次,文章对现行几种主要的区域金融评估方法进行阐述和比较,指出其适用范围和存在的缺陷。然后针对目前各种区域金融生态评估方法的局限性,借鉴其他领域的一些评估理论、流程和方法,结合区域金融生态的复杂巨系统的特点,尝试性地将组合赋权法和神经网络模型有机结合运用于区域金融生态的综合评估中,构建基于加权分层的BP神经网络评估模型。
最后,采用某省2008年度县域金融生态数据对本文提出的基于加权分层的BP神经网络评估模型进行了实证分析,结果表明本文提出的评估模型下得出的县域金融生态评估结果是有效的。并与已有的组合方法的实证分析比较,表明基于加权分层的BP神经网络评估模型在区分度、互补性、一致性上均优于已有的区域金融生态评估方法,具有较好的适用性和合理性。
Financial ecology is dynamic equilibrium system which is formed by the interaction between the financial main body, the financial main body and external financial environment.How to develop a good financial ecology in financial crisis and find the opportunity of Chinese financial industry, how to make a scientific and accurate assessment of the regional financial ecology, has become a topic of common concern both in the theory and practice fields. In this context, this dissertation aims at providing a more scientific and more reasonable method to evaluate regional financial ecology.
On the basis of a summary and analysis of the current evaluation methods of regional financial ecology, in accordance with the characteristic and evaluation goal in our country, this dissertation uses the comparative analysis method to make some exploration on the method of Chinese regional financial ecology evaluation both in theory and in practice.
First, begin with financial ecology theory, the dissertation identifies the characteristic and goal of regional financial ecology evaluation, defines the concept of regional financial ecology and regional financial ecology evaluation. On that basis, the dissertation sets the precondition as that regional financial ecology is a complex giant system, points out the problem in existing each kinds of indexes system, puts forward the region finance ecology indicator system's improvement proposal from the layered angle.
Second, the dissertation summarizes and analyses current main methods, points out the application scope and limitations of existing evaluation methods. According to the limitations of present each kind of regional financial ecology evaluation method, this dissertation learns from the theories, the process and the methods in other domains, tries to combine the combination weighting method and neural network model for regional financial ecological comprehensive assessment, and sets up the combined evaluation model based on weighted hierarchical BP neural network.
At last, the dissertation makes use of the country financial ecology data of a province to conduct an empirical analysis on the combined evaluation model based on weighted hierarchical BP neural network. The result shows that the combined evaluation model based on weighted hierarchical BP neural network is feasible and effective. Using the financial ecological data of a province in 2008, compared to the existing models, the empirical analysis and comparison shows that the proposed model which is based on weighted hierarchical BP neural network model perform well in differentiation, complementary and consistency is superior to existing regional financial ecological assessment methods, with good applicability and rationality.
本文采用比较分析方法,在对当前各种区域金融生态评估方法进行梳理比较的基础上,结合我国区域金融生态特点及区域金融生态的评估目的,对适合于我国区域金融生态评估的方法进行理论与实践上的探索。
首先,文章从金融生态理论入手,明确区域金融生态评估目的和特点,对区域金融生态概念以及区域金融生态评估进行界定。在此基础上以区域金融生态是一个复杂巨系统为前提,指出当前各种指标体系存在的问题,并从层次性角度提出区域金融生态指标体系的合理设计。
其次,文章对现行几种主要的区域金融评估方法进行阐述和比较,指出其适用范围和存在的缺陷。然后针对目前各种区域金融生态评估方法的局限性,借鉴其他领域的一些评估理论、流程和方法,结合区域金融生态的复杂巨系统的特点,尝试性地将组合赋权法和神经网络模型有机结合运用于区域金融生态的综合评估中,构建基于加权分层的BP神经网络评估模型。
最后,采用某省2008年度县域金融生态数据对本文提出的基于加权分层的BP神经网络评估模型进行了实证分析,结果表明本文提出的评估模型下得出的县域金融生态评估结果是有效的。并与已有的组合方法的实证分析比较,表明基于加权分层的BP神经网络评估模型在区分度、互补性、一致性上均优于已有的区域金融生态评估方法,具有较好的适用性和合理性。
Financial ecology is dynamic equilibrium system which is formed by the interaction between the financial main body, the financial main body and external financial environment.How to develop a good financial ecology in financial crisis and find the opportunity of Chinese financial industry, how to make a scientific and accurate assessment of the regional financial ecology, has become a topic of common concern both in the theory and practice fields. In this context, this dissertation aims at providing a more scientific and more reasonable method to evaluate regional financial ecology.
On the basis of a summary and analysis of the current evaluation methods of regional financial ecology, in accordance with the characteristic and evaluation goal in our country, this dissertation uses the comparative analysis method to make some exploration on the method of Chinese regional financial ecology evaluation both in theory and in practice.
First, begin with financial ecology theory, the dissertation identifies the characteristic and goal of regional financial ecology evaluation, defines the concept of regional financial ecology and regional financial ecology evaluation. On that basis, the dissertation sets the precondition as that regional financial ecology is a complex giant system, points out the problem in existing each kinds of indexes system, puts forward the region finance ecology indicator system's improvement proposal from the layered angle.
Second, the dissertation summarizes and analyses current main methods, points out the application scope and limitations of existing evaluation methods. According to the limitations of present each kind of regional financial ecology evaluation method, this dissertation learns from the theories, the process and the methods in other domains, tries to combine the combination weighting method and neural network model for regional financial ecological comprehensive assessment, and sets up the combined evaluation model based on weighted hierarchical BP neural network.
At last, the dissertation makes use of the country financial ecology data of a province to conduct an empirical analysis on the combined evaluation model based on weighted hierarchical BP neural network. The result shows that the combined evaluation model based on weighted hierarchical BP neural network is feasible and effective. Using the financial ecological data of a province in 2008, compared to the existing models, the empirical analysis and comparison shows that the proposed model which is based on weighted hierarchical BP neural network model perform well in differentiation, complementary and consistency is superior to existing regional financial ecological assessment methods, with good applicability and rationality.
引文
[1]白钦先等.金融可持续发展理论研究导论.北京：中国金融出版社,2002：2-6
[2]Hoggarth G,Saporta V.Costs of Banking System Instability:Some Empirical Evidence. Financial Stability Review,2001:150-155
[3]Ross Levine. Law, Finance and Economic Growth. Journal of Financial Intermediation,2002, (8):8-9
[4]徐诺金.论我国的金融生态问题.金融研究,2005,(11)：35-45
[5]周小川.完善法律制度,改进金融生态.金融时报,2004-12-11
[6]周小川.保持金融稳定防范道德风险.金融研究,2004,(4)：28-30
[7]苏宁.金融生态环境的基本内涵.金融信息参考,2005,(10)：6-7
[8]韩平.金融生态链的扣扣咬合是关键.金融时报,2005-08-05
[9]王松奇.充分认识金融生态建设的重要性.金融时报,2005-08-23
[10]杨子强.优化金融生态环境,促进地方经济发展.济南金融,2005,(5)：3-6
[11]李扬,王国刚,刘煜辉.中国城市金融生态环境评价.北京：人民出版社2005：15-34
[12]徐诺金.如何理解“金融生态”.南方金融,2006,(10)：23-26
[13]张志元,雷良海.区域金融综合竞争力研究——基于山东省17地市金融生态横截面数据的分析.济南大学学报,2006,(6)：20-25
[14]黄娜,路杨.金融生态研究：一个文献综述.经济论坛,2006,(19)：101-103
[15]徐小林.区域金融生态环境评估方法.金融研究,2005,(11)：39-45
[16]李扬,王国刚,刘煜辉.中国地区金融生态环境评价(2006-2007).北京：人民出版社,2006：75-86
[17]中国人民银行广州分行课题组.广东区域金融生态实证研究.南方金融,2006,(11)：5-8
[18]中国人民银行成都分行.区域金融生态环境测评研究—对成都市县域金融生态环境的测评明.西南金融,2006,(7)：23-25
[19]中国人民银行洛阳市中心支行课题组.区域金融生态环境评估指标体系研究.金融理论与实践,2006,(1)：10-13
[20]人行德阳市中心支行.金融生态环境评估指标体系的构建.西南金融,2006,(11)：35-36
[21]汪祖杰等.区域金融生态环境质量评估指标体系研究.金融研究,2006,(5)：150-158
[22]张瑞怀.基于BP神经网络模型的农村金融生态环境综合评估.行长论坛,2006,(10)：29-31
[23]张晓峰.区域金融生态环境评估指标体系研究.金融经济,2007,(5)：111-113
[24]湖南大学金融管理研究中心.2007年度株洲市县域金融生态评估报告.株洲日报,2008-09-05
[25]人行张家界市中心支行课题组.金融生态的层次结构与金融资源均衡配置：张家界个案分析.金融研究,2005,(11)：156-163
[26]Anderson T W. An introduction to multivariate statistical analysis[M].2nd edition, New York:John Wiley&Sons, Inc,1984,5-25
[27]Saaty,T.L. The Analytic Hierarchy Process. McGraw Hill,1980:21-27
[28]李明远.多指标决策与评估的新方法—主成分投影法.数理统计与管理,2000,20(5)：45-48
[29]吴治民,姜涛,张长全.安徽省县域金融生态综合评价研究.铜陵学院学报,2008,(3)：36-38
[30]殷仲民,杨沁,张琼.西安市金融生态环境的评价.当代经济,2008,(2)：82-83
[31]Coo K W D,Roll Y,Kaxakov A.A DEA model for frontier decision making units in DEA.IN FORS,1994,59(2):31-32
[32]胡守仁.神经网络导论.长沙：国防科技大学出版社,1993：126-130
[33]杜栋,庞庆华,吴炎.现代综合评估方法与案例精选.北京：清华大学出版社,2008：33-34
[34]Ma J,Fan Z P,Huang L H.A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research,1999, 112:397-404
[35]汪应洛.系统工程(第2版).北京：机械工业出版社,2001：45-71
[36]郭金龙.复杂系统范式视角下的金融演进与发展.北京：中国金融出版社,2007：55-61
[37]金菊良,魏一鸣,丁晶.基于组合权重的系统评估模型.数学的实践与认识,2003,33(11)：51-56
[38]Geman S. Neural networks and bias/variance dilemma. Neural Computation, 1992, (4):1-58
[39]彭汉川,甘强,韦钰.提高前馈神经网络推广能力的若干实际方法.电子学报,1998,(4)：116-119
[40]Baldi P. Temporal evolution of generalization during learning in linear networks. Neural Computation.1991,3:589-603
[41]张立明.人工神经网络的模型及应用.上海：复旦大学出版社,2003：182-191
[42]姜玉山,朱孔来.现代化评估指标体系及综合评估方法.统计研究,2002,(1)：50-54
[43]冯端,冯步云.熵.北京：科学出版社,1992：69-77
[44]Fornell.Claes and David F.Larcker. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 1981,(18),39-50
[45]Saaty,T.L.The Analytic Network Process.RWS Publications,1996:19-33
[2]Hoggarth G,Saporta V.Costs of Banking System Instability:Some Empirical Evidence. Financial Stability Review,2001:150-155
[3]Ross Levine. Law, Finance and Economic Growth. Journal of Financial Intermediation,2002, (8):8-9
[4]徐诺金.论我国的金融生态问题.金融研究,2005,(11)：35-45
[5]周小川.完善法律制度,改进金融生态.金融时报,2004-12-11
[6]周小川.保持金融稳定防范道德风险.金融研究,2004,(4)：28-30
[7]苏宁.金融生态环境的基本内涵.金融信息参考,2005,(10)：6-7
[8]韩平.金融生态链的扣扣咬合是关键.金融时报,2005-08-05
[9]王松奇.充分认识金融生态建设的重要性.金融时报,2005-08-23
[10]杨子强.优化金融生态环境,促进地方经济发展.济南金融,2005,(5)：3-6
[11]李扬,王国刚,刘煜辉.中国城市金融生态环境评价.北京：人民出版社2005：15-34
[12]徐诺金.如何理解“金融生态”.南方金融,2006,(10)：23-26
[13]张志元,雷良海.区域金融综合竞争力研究——基于山东省17地市金融生态横截面数据的分析.济南大学学报,2006,(6)：20-25
[14]黄娜,路杨.金融生态研究：一个文献综述.经济论坛,2006,(19)：101-103
[15]徐小林.区域金融生态环境评估方法.金融研究,2005,(11)：39-45
[16]李扬,王国刚,刘煜辉.中国地区金融生态环境评价(2006-2007).北京：人民出版社,2006：75-86
[17]中国人民银行广州分行课题组.广东区域金融生态实证研究.南方金融,2006,(11)：5-8
[18]中国人民银行成都分行.区域金融生态环境测评研究—对成都市县域金融生态环境的测评明.西南金融,2006,(7)：23-25
[19]中国人民银行洛阳市中心支行课题组.区域金融生态环境评估指标体系研究.金融理论与实践,2006,(1)：10-13
[20]人行德阳市中心支行.金融生态环境评估指标体系的构建.西南金融,2006,(11)：35-36
[21]汪祖杰等.区域金融生态环境质量评估指标体系研究.金融研究,2006,(5)：150-158
[22]张瑞怀.基于BP神经网络模型的农村金融生态环境综合评估.行长论坛,2006,(10)：29-31
[23]张晓峰.区域金融生态环境评估指标体系研究.金融经济,2007,(5)：111-113
[24]湖南大学金融管理研究中心.2007年度株洲市县域金融生态评估报告.株洲日报,2008-09-05
[25]人行张家界市中心支行课题组.金融生态的层次结构与金融资源均衡配置：张家界个案分析.金融研究,2005,(11)：156-163
[26]Anderson T W. An introduction to multivariate statistical analysis[M].2nd edition, New York:John Wiley&Sons, Inc,1984,5-25
[27]Saaty,T.L. The Analytic Hierarchy Process. McGraw Hill,1980:21-27
[28]李明远.多指标决策与评估的新方法—主成分投影法.数理统计与管理,2000,20(5)：45-48
[29]吴治民,姜涛,张长全.安徽省县域金融生态综合评价研究.铜陵学院学报,2008,(3)：36-38
[30]殷仲民,杨沁,张琼.西安市金融生态环境的评价.当代经济,2008,(2)：82-83
[31]Coo K W D,Roll Y,Kaxakov A.A DEA model for frontier decision making units in DEA.IN FORS,1994,59(2):31-32
[32]胡守仁.神经网络导论.长沙：国防科技大学出版社,1993：126-130
[33]杜栋,庞庆华,吴炎.现代综合评估方法与案例精选.北京：清华大学出版社,2008：33-34
[34]Ma J,Fan Z P,Huang L H.A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research,1999, 112:397-404
[35]汪应洛.系统工程(第2版).北京：机械工业出版社,2001：45-71
[36]郭金龙.复杂系统范式视角下的金融演进与发展.北京：中国金融出版社,2007：55-61
[37]金菊良,魏一鸣,丁晶.基于组合权重的系统评估模型.数学的实践与认识,2003,33(11)：51-56
[38]Geman S. Neural networks and bias/variance dilemma. Neural Computation, 1992, (4):1-58
[39]彭汉川,甘强,韦钰.提高前馈神经网络推广能力的若干实际方法.电子学报,1998,(4)：116-119
[40]Baldi P. Temporal evolution of generalization during learning in linear networks. Neural Computation.1991,3:589-603
[41]张立明.人工神经网络的模型及应用.上海：复旦大学出版社,2003：182-191
[42]姜玉山,朱孔来.现代化评估指标体系及综合评估方法.统计研究,2002,(1)：50-54
[43]冯端,冯步云.熵.北京：科学出版社,1992：69-77
[44]Fornell.Claes and David F.Larcker. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 1981,(18),39-50
[45]Saaty,T.L.The Analytic Network Process.RWS Publications,1996:19-33