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银行间市场风险传染机制与免疫策略研究
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摘要
银行间市场是现代金融系统的重要组成部分,也是整个金融系统健康稳定运行不可或缺的金融中介市场。在银行个体层面上,银行间市场可以调节单个银行的流动性盈余和短缺,例如流动性盈余的银行可以为流动性短缺的银行提供资金借贷。在金融系统层面上,银行间市场能反映出整个金融市场的资金供求状况,并为中央银行制定和实施货币政策提供平台,例如实施公开市场操作等等。然而,银行间市场在发挥其不可替代作用的同时,也不可避免地提高了银行主体之间风险头寸暴露的相关性。毫无疑问,这将给银行系统带来潜在风险,因为它为银行倒闭时的风险传染提供了途径。
     目前,中国的银行间市场发展迅速。如何避免银行风险传染的发生,并确保金融系统的稳定,一直是中国金融监管当局重视的问题。一方面,我国正不断推进金融改革,扩大金融对外开放,外资银行也将全面进入中国。这样,国内银行与外资银行之间的联系将变得更加紧密。这可能为银行风险传染提供新的途径。另一方面,中国银行间市场的规模和成员数量都在不断增加,且交易形式和交易工具更加复杂多样。因此,在银行间市场中,银行主体之间通过信用连接形成了一种复杂的借贷关系,即一种复杂的银行间信用网络结构关系。这无疑为银行监管提出了新的挑战。因此,在这种新形势下,研究和认识银行间市场中的风险传染机制显得尤为重要。
     然而,现有对银行间市场中银行风险传染的研究大多停留在进行一些定性和实例分析,而对银行风险传染机制的定量研究仍很缺乏。本论文正是从银行间市场结构与功能的关系出发,提出了一个基于网络理论的定量分析框架,对银行间市场中的风险传染机制及风险传染免疫策略等问题进行了系统的研究。
     本研究的主要工作及由此形成的结论包括:
     一、综述了目前国内外对银行风险传染的已有研究成果。本论文首先总结了对银行间市场结构特征的已有研究。其次,对银行间市场中风险传染的实证和理论研究进行了全面的梳理和综述。另外,本文进一步总结了有关银行风险传染的实证研究方法,并分析了其存在的不足。最后,在总结现有研究的基础上,本论文指出,结合网络理论来研究银行风险传染问题是目前有关银行风险传染研究的新趋势。
     二、建立了基于网络理论的银行间市场结构模型。本论文运用网络理论来描述银行间市场结构,全面介绍了银行间市场的各种网络结构模型,如随机银行网络模型、小世界银行网络模型、无标度银行网络模型等。此外,基于现有的实证研究结果,本文提出了双幂律银行网络结构模型。本论文研究认为,银行网络中这种双幂律度分布现象存在的机制及其经济含义是:信用拆借能力相近的银行之间更易于建立信用拆借关系。进一步,本论文对银行网络模型的微观结构特征进行了深入的比较研究。结果显示,在具有不同宏观结构特征的银行网络中,其微观Motif结构的类型和数量通常存在很大的差异。
     三、建立了基于资产负债表的银行主体行为模型。在给定的银行间信用拆借分布假定条件下,由银行间资产比例、银行流动性资产比例和银行资产净值比例三个参数,确定了银行间市场中各银行主体的资产负债表结构,从而建立起一个描述该市场中银行主体行为的分析模型。在此模型基础上,本论文对银行间市场中基于资产负债表连接的银行风险传染过程进行了深入分析。
     四、建立了基于宏观结构(Macro-Structure)和微观主体(Micro-Agent)相结合的银行风险传染定量分析框架。以银行网络结构模型和银行主体行为模型为基础,基于“将宏观结构和微观主体相结合”的分析思想,本论文系统全面地提出了研究银行风险传染的定量分析框架(即MS-MA分析框架)。进一步,给出了MS-MA分析框架下银行风险传染的定量分析方法和分析过程。
     五、研究了基于MS-MA分析框架的银行风险传染机制。在MS-MA定量分析框架下,本论文分别研究了银行网络结构和银行主体行为与银行风险传染机制之间的关系。此外,基于不同的传染冲击方式,本论文分别对基于违约冲击和基于分摊初始冲击等传染冲击方式下的银行风险传染机制进行了研究。研究结果表明,从长期来看,银行间市场成员规模的扩张有利于降低银行间市场中的风险传染效应。另外,在成员规模较大的银行间市场中,与银行主体只拆入或只拆出资金相比,银行主体同时参与资金的拆入和拆出能有效地分散自身和其他银行主体的风险暴露,从而降低银行间市场中的风险传染效应。此外,采取分散化措施能否有效地降低银行风险传染效应,这要取决于银行间市场当前所处的状态和市场结构特征。
     六、研究了基于MS-MA分析框架的银行风险传染免疫策略。在MS-MA定量分析框架下,对银行风险传染的目标免疫策略、净额免疫策略、银行间救助免疫策略和组合免疫策略进行了研究。对目标免疫策略的研究发现,资产规模大且连接度高的银行通常应该首先被免疫,因为它们“具有太大的系统性冲击能力而不能失败”(即Too Systemic To Fail)。另外,与未采用免疫策略相比,采用净额免疫策略、银行间救助免疫策略或组合免疫策略通常都能取得较好的免疫效果。然而,在相同的传染冲击方式和银行网络结构下,不同的免疫策略其免疫效果存在差异。综合地来考虑,组合免疫策略通常会具有较理想的免疫效果。
     本研究的创新性体现在以下三个方面:
     一、建立了描述银行间市场结构的双幂律银行网络结构模型。实证研究发现,银行间市场具有双幂律度分布特征,但一直没有理论模型对此进行解释。本论文提出了一个银行网络生长模型,解释了这种双幂律度分布现象存在的机制及其经济含义,即信用拆借能力相近的银行之间更易于建立信用拆借关系。(该成果发表于国际英文SCI专业学术期刊)
     二、建立了基于MS-MA的银行风险传染定量分析框架。银行风险传染问题的研究目前仍没有统一的定量分析框架。本论文基于“宏观结构和微观主体相结合”的思想,将银行网络的宏观结构模型和基于资产负债表的银行微观主体行为模型相结合,系统地提出和阐述了研究银行风险传染问题的定量分析框架。
     三、基于MS-MA分析框架,定量地研究了银行风险传染机制与免疫策略问题。一方面,本论文分别定量地研究了银行间市场结构和银行主体行为与银行风险传染机制之间的关系,且基于不同的传染冲击方式,分别对基于违约冲击和基于分摊初始冲击等传染冲击方式下的银行风险传染机制进行了研究。另一方面,本论文提出并研究了控制银行风险传染的目标免疫策略、净额免疫策略、银行间救助免疫策略和组合免疫策略等,并进一步对不同市场结构下的免疫策略进行了比较研究。
Interbank market is an essential financial intermediate for financial system to function healthily and stably, and is also an important component of modern financial systems. In individual aspect, interbank market can regulate the liquidity surplus or short for individual bank, such as the banks with liquidity surplus can lend to the banks with liquidity short. In financial system aspect, capital supply and demand of financial market can be reflected through interbank market. In this way, it will provide central bank a platform to establish and implement monetary policy, such as the open market operations. However, at the time to exert its function, interbank market increased the relativity between the risk exposures of banks. Out of question, it will present banking system potential risks, and will provide paths for risk contagion in bank failure.
     At present, Chinese interbank market develops rapidly. How to avoid risk contagion in banking systems is always an important problem faced with Chinese financial regulators. On the one hand, China is promoting financial reform step by step, and foreign banks will also participate in Chinese financial market. In this way, there will be a more close relationship between foreign banks and the banks in the country. This will also provide new paths for bank risk contagion. On the other hand, the market scales and the members are all increasing in Chinese interbank market, and furthermore, the financial tools and the trade forms are more and more complex. Therefore, a complex relationship of lending and borrowing between bank agents will be formed in interbank market. This will put forward new challenges for bank regulation definitely. Consequently, with these new positions, it is important to study and understand the mechanisms of risk contagion in interbank market.
     However, most of the researches in banking risk contagion are focused on qualitative or empirical analysis till now. It is devoid of quantitative analysis in the research fields of bank contagion. In the view of the relationship between the structure and function of interbank market, this paper presents a quantitative framework for the analysis of banking risk contagion. Specially, the quantitative framework is put forward based on network theory. In this framework, we have studied the risk contagion mechanisms and immunization strategies systematically.
     The main work and conclusions are presented as following:
     1. This paper summarized the existed literatures on studies of bank risk contagion. Firstly, we reviewed existed researches on the features of interbank market structures. Secondly, this paper summarized empirical and theoretical studies on bank contagion in detail. Moreover, empirical methods on the research of bank contagion have been reviewed, and the shortages of the methods also presented. Finally, with the reviews in this paper, we point out that, the latest directions in the research of the issues on bank contagion are the studies based on network theories.
     2. A banking network model used to describe the structures of interbank market is presented in this dissertation. In this paper, the network theory is used to describe the structures of interbank market. In this way, most of the interbank network models have been wholly introduced to describe interbank market, such as random banking network model, small-world banking network model and scale-free banking network model, etc. Moreover, based on the existed empirical results, we put forward a two-power-law banking network model in this paper. In our research, we study the mechanism for the existence of the two-power-law phenomenon. Additionally, we explain the economic significance of this result is that, the closer of the interbank lending and borrowing ability between two banks, the easier they will establish a relationship of interbank lending and borrowing. Furthermore, comparative studies on micro-structures between banking network models have been presented in this paper. Our results reveal that, in the banking network models with different macro-structure features, there are great differences in types and amounts of micro-structures.
     3. A bank agent model based on balance-sheet connections is put forward in this paper. Given the distribution function of interbank credit liabilities, and with three parameters such as p、q and m, we can obtain the balance-sheet structures of all banks in interbank market. In this way, we put forward an agent model to describe the behavior of a bank in interbank market. Furthermore, based on this agent model, the analysis of bank contagion based-on balance-sheet connections has been given.
     4. A quantitative framework is presented through combing the Macro-Structure of interbank market and the Micro-Agent of banks. Based on the banking network model and the bank agent model, and with the thoughts of combining the Macro-Structure of interbank market and Micro-Agent behavior of banks, a quantitative framework has been presented for the analysis of banking contagion. That is the MS-MA framework. Furthermore, we put forward the quantitative analysis method for bank contagion under the MS-MA framework.
     5. We studied mechanisms of bank risk contagion base-on the MS-MA framework. Under the MS-MA framework, this paper studied how the banking network structure and bank agent behavior influences the mechanisms of bank risk contagion. Moreover, with different patterns of contagion, we analyzed the bank contagion process respectively based on default pattern and the pattern of initial shock apportion. Our results indicate that, in the long term, increasing in the member size of interbank market can help to lower the contagion effect in the market. Moreover, in the interbank market with large member size, bank agent both participating in interbank lending and borrowing can help to reduce risk exposures and decrease contagion effects more effectively, comparing with the bank agent only take part in interbank lending or borrowing. Furthermore, whether the decentralization measures can effectively lower the contagion effect relies on the states and structure features of the interbank market.
     6. The immunization strategies of bank risk contagion have been studied under the MS-MA framework in this paper. Under the quantitative framework, we have studied the target immunization strategy、the netting immunization strategy、the interbank bailout immunization strategy and the mix immunization strategy. With the research of the target strategy, it reveals that the banks with large size of bank assets and high degree of connections should be immunized firstly. Because these banks will produce huge shocks to banking network system when it failed, so it cannot be failed. This means Too Systemic To Fail. Moreover, comparing with no immunization strategies, taking the strategies such as the netting strategy、the interbank bailout strategy or the mix strategy can all obtain a better immunization effect. However, with the same pattern of contagion and the same structure features of interbank market, different immunization strategy will produce different immunization effect. With synthetic consideration, mix strategy can generally obtain a better immunization effect.
     The innovative points of this dissertation are as following:
     1. This paper put forward a two-power-law banking network model to describe the structure of interbank market. Empirical study reveals the existence of the two-power-law degree distribution in interbank market, but no theoretical model to explain this phenomenon. In our research, we put forward a network growth model and study the mechanism for the existence of the two-power-law phenomenon. Additionally, we explain the economic significance of this result is that, the closer of the interbank lending and borrowing ability between two banks, the easier they will establish a relationship of interbank lending and borrowing.
     2. A quantitative framework has been presented for the analysis of bank contagion. Presently, there is no quantitative framework for the analysis of banking risk contagion. In this paper, we systematically put forward a quantitative framework to analyze the problems of bank contagion, based on the thoughts of combining the Macro-Structure of the interbank market and Micro-Agent behavior of the banks. In detail, this framework is presented based on two models, that is the banking network model and the bank agent model.
     3. Based on the MS-MA framework, banking risk contagion and immunization strategies have been quantitatively studied in this paper. On the one hand, how the structures of interbank market and the behaviors of banks affect the banking risk contagion process has been studied quantitatively. And moreover, under the different patterns of risk contagion, we analyzed the bank contagion process respectively based on default pattern and the pattern of initial shock apportion. On the other hand, to control the banking risk contagion process, four immunization strategies such as the target immunization strategy、the netting immunization strategy、the interbank bailout immunization strategy and the mix immunization strategy have been put forward in this paper. Furthermore, immunization effects of the strategies have been studied under different structures of interbank market.
引文
1. Adamic, L.A., and B.A. Huberman. Power-law Distribution of the World Wide Web [J]. Science, 2000, 287: 2115.
    2. Aghion, P., P. Bolton, and M. Dewatripont. Contagious Bank Failures in a Free Banking System [J]. European Economic Review, 2000, 44: 713-718.
    3. Aharony, J. and I. Swary. Additional Evidence on the Information-based Contagion Effects of Bank Failures [J]. Journal of Banking & Finance, 1996, 20: 57-69.
    4. Akhigbe, A., and J. Madura. Why do Contagion Effects Vary Among Bank Failures? [J], Journal of Banking & Finance, 2001, 25: 657-680.
    5. Albert, R., and A.-L. Barabasi. Statistical Mechanics of Complex Networks [J]. arXiv: cond-mat/0106096, 2001.
    6. Albert, R., H. Jeong and A.-L. Barabasi. Diameter of the World-Wide-Web [J]. Nature, 1999, 401: 130-131.
    7. Albert, R., H. Jeong and A.-L. Barabasi. Error and Attack Tolerance of Complex Networks [J]. Nature, 2000, 406: 378-382.
    8. Aleksiejuk, A., and J.A. Holyst. A Simple Model of Bank Bankruptcies[J]. Physica A, 2001, 299: 198-204.
    9. Aleksiejuk, A., J.A. Holyst and G. Kossinets. Self-organized Criticality in a Model of Collective Bank Bankruptcies [J]. International Journal of Modern Physics C, 2002, 13(3): 333-341.
    10. Alentorn, A., E. Nier and J. Yang. Network Models and Financial Stability [J]. University of Essex, Working paper, 2005.
    11. Allen, F., and D. Gale. Financial Contagion [J]. Journal of Political Economy, 2000, 108: 1-34.
    12. Allen, F., and D. Gale. Competition and Financial Stability [R]. prepared for the World Bank and Federal Reserve Bank of Cleveland project on Bank Concentration, 2003.
    13. Amaral, L.A.N., P. Gopikrishnan, V. Plerou, and H.E. Stanley. A Model for the Growth Dynamics of Economic Organizations [J]. Physica A, 2001, 299: 127-136.
    14. Amundsen E., H. Arnt. Contagion Risk in the Danish Interbank Market [J]. Danmarks NationalBank Working Paper, No.29, 2005.
    15. Angelini, P., G. Maresca, and D. Russo. Systemic Risk in the Netting System [J]. Journal of Banking and Finance, 1996, 20: 853-886.
    16. Arthur, W.B. Complexity and the Economy [J]. Science, 1999, 284: 107-109.
    17. Axtell, R.L. Zipf Distribution of US Firm Sizes [J]. Science, 2001, 293: 1818-1820.
    18. Balthrop, J., S. Forrest, M.E. Newman and M.M. Williamson. Technological Networks and the Spread of Computer Viruses [J]. Science, 2004, 304: 527-529.
    19. Barabasi, A.-L., and R. Albert. Emergence of Scaling in Random Networks [J]. Science, 1999, 286: 509-512.
    20. Basel Committee on Banking Supervision. The New Basel Capital Accord [R]. URL: www.bis.org, 2001.
    21. Bech M. L., B. Madsen, L. Natorp. Systemic Risk in the Danish Interbank Nettinig System [J]. Danmarks NationalBank Working Paper, No.8, 2002.
    22. Blavarg M., P. Nimander. Interbank Exposures and Systemic Risk [J]. Economic Review, 2002, 2: 19-45.
    23. Boss, M., H. Elsinger, M. Summer and S. Thurner. An Empirical Analysis of the Network Structure of the Austrian Interbank Market [R]. OeNB Financial Stability Report 7, 2003: 77-87.
    24. Boss, M., H. Elsinger, M. Summer and S. Thurner. The Network Topology of the Interbank Market [J]. arXiv:cond-mat/0309582, 2003.
    25. Boss, M., M. Summer and S. Thurner. Contagion Flow Through Banking Networks [J]. arXiv: cond-mat/0403167, 2004.
    26. Boss M., H. Elsinger, M. Summer and S. Thurner. Network Topology of the Interbank Market [J]. Quantitative Finance, 2004, 4: 677-684.
    27. Bouchaud, J.P. Power-laws in Economics and Finance: Some Ideas from Physics [J]. Quantitative Finance, 2001, 1: 105-112.
    28. Bougheas, S. Contagious Bank Runs [J]. International Review of Economics & Finance, 1999, 8: 131-146.
    29. Calomiris, C., and J. Mason. Contagion and Bank Failures During the Great Depression: The June 1932 Chicago Banking Panic [J]. American Economic Review, 1997, 87(5): 863-883.
    30. Cancho, R.F., and R.V. Sole. Two Regimes in the Frequency of Words and the Origins of Complex Lexicons: Zipf’s Law Revisited [J]. SFI Working paper, 2001.
    31. Cancho, R.F., and R.V. Sole. The Small-World of Human Language [J]. SFI Working paper, 2001.
    32. Cartwright, E. The Stability of Conventions: Random and Lattice Matching Networks Compared [J]. Economics Letters, 2004, 85: 47-51.
    33. Cassar A., N. Duffy. Contagion of Financial Crises under Local and Global Networks [J]. In Agent-Based Methods in Economics and Finance: Simulations in Swarm, edited by Francesco Luna and Alessandro Perrone, Kluwer Academic Publishers, 2001.
    34. Chari, V.V., and R. Jagannathan. Banking Panics, Information, and Rational ExpectationEquilibrium [J]. Journal of Finance, 1988, 43(3): 749-761.
    35. Cifuentes, R. Banking Concentration: Implications for Systemic Risk and Safety Net Design [J]. Central Bank of Chile Working paper, No. 231, 2003,
    36. Cifuentes, R., G. Ferrucci and H.S. Shin. Liquidity Risk and Contagion[J]. Workshop “Accounting, Transparency and Bank Stability”, Bank for International Settlements, 2004.
    37. Dasgupta, A. Financial Contagion Through Capital Connections: A Model of the Origin and Spread of Bank Panic [J], Mimeo, 2002.
    38. Davis, M., and V. Lo. Infectious Defaults [J]. Quantitative Finance, 2001,1: 382-387.
    39. Degryse, H., and G. Nguyen. Interbank Exposures: An Empirical Examination of Systemic Risk in the Belgian Banking System [J]. National Bank of Belgium Working paper, 2004, 43.
    40. De Masi G., G. Iori, G. Caldarelli. Fitness Mode for the Italian Interbank Money Market [J]. Phys. Rev. E, 2006, 74, 066112.
    41. De Vries, C.G. The Simple Economics of Bank Fragility [J]. Journal of Banking & Finance, 2005, 29: 803-825.
    42. Diamond, D.W., and P.H. Dybvig. Bank Runs, Deposit Insurance, and Liquidity [J], Journal of Political Economy, 1983, 91: 401-419.
    43. Diamond, D., and R. Rajan. Liquidity Risk, Liquidity Creation, and Financial Fragility: A Theory of Banking [J]. Journal of Political Economy, 2001, 109(2): 287-327.
    44. Dodds, P.S., R. Muhamad and D.J. Watts. An Experimental Study of Search in Global Social Networks [J]. Science, 2003, 301: 827-829.
    45. Dorogovtsev, S.N., and J.F.F. Mends. Evolution of Networks [J]. arXiv:cond-mat/0106144, 2001.
    46. Dorogovtsev, S.N., and J.F.F. Mends. Language as an Evolving Word Web [J]. arXiv:cond-mat/0105093, 2001.
    47. Dorogovtsev, S.N., and J.F.F. Mends. Accelerated Growth of Networks [J]. arXivf:cond-mat/0204102, 2002.
    48. Dow, J. What is Systemic Risk? Moral Hazard, Initial Shocks and Propagation [J]. Monetary and Economic Studies, 2000, 18(2): 1-24.
    49. Eisenberg, L. Connectivity and Financial Network Shutdown [J]. SFI Working paper, 1995.
    50. Eisenberg, L., and T. Noe. Systemic Risk in Financial System [J]. Management Science, 2001, 47: 236-249.
    51. Elsinger, H., A. Lehar, and M. Summer. A New Approach to Assessing the Risk of Interbank Loans [R]. OeNB Financial Stability Report 3, 2002: 75-86.
    52. Elsinger, H., A. Lehar, and M. Summer. Risk Assessment for Banking Systems [J]. OeNB Working paper, 2003, 79.
    53. Emmons W. R.. Interbank Netting Agreements and the Distribution of Bank Default Risk [J]. Federal Reserve Bank of St. Louis Working Paper, 1995, 95-016A.
    54. Frauendorfer, K., and P. Gantenbei. Banks and Contagion Risks [J]. Paper for the Doctorate Seminar “International Finance”, University of St. Gallen, 2001.
    55. Freixas, X., and B. Parigi. Contagion and Efficiency in Gross and Net Interbank Payment Systems [J]. Journal of Financial Intermediation, 1998, 7: 3-31.
    56. Freixas, X., B. Parigi, and J.C. Rochet. Systemic Risk, Interbank relations and Liquidity Provision by the Central Bank [J]. Journal of Money, Credit, and Banking, 2000, 32(3): 611-638.
    57. Fujiwara, Y. Zipf Law in Firms Bankruptcy [J]. Physica A, 2004, 337: 219-230.
    58. Furfine, C. Interbank Exposures: Quantifying the Risk of Contagion [J]. BIS Working paper, No.70, 1999.
    59. Furfine, C. Interbank Exposures: Quantifying the Risk of Contagion [J]. Journal of Money, Credit, and Banking, 2003, 35: 111-128.
    60. Galos P., K. Soramaki. Systemic Risk in Alternative Payment System Designs [J]. European Central Bank Working Paper, No.508, 2005.
    61. Garlaschelli, D., and M.I. Loffredo. Wealth Dynamics on Complex Networks [J]. Physica A, 2004, 338: 113-118.
    62. Hernandez, L., and R. Valdes. What Drives Contagion: Trade, Neighborhood, or Financial Links? [J]. IMF Working paper, No.0129, 2001.
    63. Huberman, B.A., and L. Adamic. Growth Dynamics of the World-Wide-Web [J]. Nature, 1999, 401: 131.
    64. Humphrey, D.B. Payments Finality and Risk of Settlement Failure [J]. in A Saunders and L. White (eds), Technology, and the Regulation of Financial Markets: Securities, Futures, and Banking, Lexington Books, Lexington, MA, 1986, 97-120.
    65. Imam M. The Chinese Interbank Markets: Cornerstone of Financial Liberalization [J]. China & World Economy, 2004, 5: 17-33.
    66. Inaoka, H., T. Ninomiya and K. Taniguchi. Fractal Network Derived from Banking Transaction: An Analysis of Network Structures Formed by Financial Institutions [J], Bank of Japan Working paper, No.04-E-04, 2004.
    67. Inaoka, H., H. Takayasu and T. Shimizu. Self-similarity of Banking Network [J]. Physica A, 2004, 339: 621-634.
    68. Iori G. An Analysis of Systemic Risk in Alternative Securities Settlement Architectures [J]. European Central Bank Working Paper, No.404, 2004.
    69. Iori, G. Criticality in a Model of Banking Crises [J]. arXiv:con-mat/0104080, 2001.
    70. Iori, G. Interbank Lending and Systemic Risk [J]. Journal of Economic Behavior & Organization, 2003, Accepted.
    71. Iori G., G. De Masi, O. V. Precup. A Network Analysis of the Italian Overnight Money Market [J]. City University of London Working Paper, July 27, 2005.
    72. Iori G., R. Renò, G. De Masi. Trading Strategies in the Italian Interbank Market [J]. City University of London Working Paper, No.06/03, 2006.
    73. Iyer R., J. L. Peydro-Alcalde. Interbank Contagion: Evidence from Real Transactions [J]. INSEAD Working Paper, 2005.
    74. Jacklin, C.J., and S. Bhattacharya. Distinguishing Panics and Information-based Bank Runs: Welfare and Policy Implications [J]. Journal of Political Economy, 1988, 96: 568-592.
    75. James, C. The Losses Realized in Bank Failures [J]. Journal of Finance, 1991, 46(4): 1223-1242.
    76. Jayanti, S.V., A.M. Whyte, and A.Q. Do. Bank Failures and Contagion Effects: Evidence from Britain and Canada [J]. Journal of Economics and Business, 1996, 48: 103-116.
    77. Jeong, H., S.P. Mason and A.L. Barabasi. Lethality and Centrality in Protein Networks [J]. Nature, 2001, 411: 41.
    78. Jeong, H., B. Tombor and R. Alber. The Large-Scale Organization of Metabolic Networks [J]. Nature, 2000, 407: 651-654.
    79. Kaminsky, G., and C. Reinhart. On Crises, Contagion, and Confusion [J]. Journal of International Economics, 1998, 51: 145-168.
    80. Kaufman, G. Bank Contagion: A Review of the Theory and Evidence [J]. Journal of Financial Service Research, 1994, 8: 123-150.
    81. Kaufman, G. Bank Failures, Systemic Risk, and Bank Regulation [J]. Federal Reserve Bank of Chicago Working paper, 96-1, 1996.
    82. Kim, H.J., and I.M. Kim. Scale-free Network in Stock Markets [J]. Journal of Korean Phys. Soc, 2002, 40: 1105.
    83. Kiyotaki, N., and J., Moore. Credit Chains [J]. University of Minnesota and London School of Economics. 1997a, mimeo.
    84. Kleiberg, J.M. Navigation in a Small World [J]. Nature, 2000, 406: 845.
    85. Kleiberg, J., and S. Lawrence. The Structure of the Web [J]. Science, 2001, 294: 1849-1850.
    86. Kyle, A., and W. Xiong. Contagion as a Wealth Effect [J]. Journal of Finance, 2001, 56: 1401-1440.
    87. Lagunoff, R., and S.L. Schreft. A Model of Financial Fragility [J]. Journal of Economic Theory, 2001, 99: 220-264.
    88. Leitner, Y. A Lifeline for the Weakest Link? Financial Contagion and Network Design [J].Federal Reserve Bank of Philadelphia Business Review, Q4, 2002.
    89. Leitner, Y. Fragile Financial Networks: Contagion, Commitment, and Private-Sector Bailouts [J]. The Journal of Finance, 2005, 60, 6: 2925-2953.
    90. Lelyveld I. V., F. Liedorp. Interbank Contagion in the Dutch Banking Sector [J]. De Nedelandsche Bank Working Paper, No.5, 2004.
    91. Li, X., Y.Y. Jin and G. Chen. Complexity and Synchronization of the World Trade Web [J]. Physcia A, 2003, 328: 287-296.
    92. Liljeros, F., C.R. Edling and L.A. N. Amaral. The Web of Human Sexual Contacts [J]. Nature, 2001, 411: 907-908.
    93. Lux, T., and M. Marchesi. Scaling and Criticality in a Stochastic Multi-agent Model of a Financial Market [J]. Nature, 1999, 397: 498-500.
    94. Milo, R., S. Itzkovitz and N. Kashtan. Superfamilies of Evolved and Designed Networks [J]. Science, 2004, 303: 1538-1542.
    95. Milo, R., S. Shen-Orr and S. Itzkovitz. Network Motifs: Simple Building Blocks of Complex Networks [J]. Science, 2002, 298: 824-827.
    96. Morris, S. Contagion, Review of Economic Studies [J], 2000, 67: 57-78.
    97. Muller, J. Two Approaches to Assess Contagion in the Interbank Market [J]. Swiss National Bank Working paper, 2003.
    98. Newman, M.E. The Structure and Function of Complex Networks [J]. SIMA Review, 2003, 45(2): 167-256.
    99. Nguyen, G. The Belgian Interbank Market: Interbank Linkages and Systemic Risk [J]. National Bank of Belgium Financial Stability Review, 2003, 105-123.
    100. Northcott C. A. Estimating Settlement Risk and the Potential for Contagion in canada’s Automated Clearing Settlement System [J]. Bank of Canada Working Paper No.41, 2002.
    101. Oliver, D.B., and P. Hartmann. Systemic Risk: a Survey [J]. European Central Bank Working paper, No.35, 2000.
    102. Oltbai, Z.N., and A.L. Barabasi. Life’s Complexity Pyramid [J]. Science, 2002, 298: 763-764.
    103. Paul, G., T. Tanizawa and S. Havlin. Optimization of Robustness of Complex Networks [J]. Eur. Phys. J. B., 2004, 38: 187-191.
    104. Pericoli, M., and M. Sbracia. A Primer on Financial Contagion [R]. URL: www.worldbank.org/contagion, 2001.
    105. Postlewaite, A., and X. Vives. Bank Runs as an Equilibrium Phenomenon [J]. Journal of Political Economy, 1987, 95: 458-491.
    106. Pritsker, M. The Channels for Financial Contagion [R]. URL: www.worldbank.org/contagion, 1999.
    107. Pushkin, D.O., and H. Aref. Bank mergers as Scale-free Coagulation [J]. Physica A, 2004, 336: 571-584.
    108. Ravasz, E., A.L. Somera and D.A. Mongru. Hierarchical Organization of Modularity in Metabolic Networks [J]. Science, 2002, 297: 1551-1555.
    109. Resendis-Antonio, O., and J. Collado-Vides. The Growth of Random Networks as a Diffusion Process [J]. Physica A, 2004, 342: 551-560.
    110. Rochet, J.C., and J. Tirole. Interbank Lending and Systemic Risk [J]. Journal of Money, Credit, and Banking, 1996, 28: 733-762.
    111. Saez, L., and X. Shi. Liquidity Pools, Risk Sharing, and Financial Contagion [J]. Journal of Financial Services Research, 2004, 25: 5-23.
    112. Santor, E. Banking Crises and Contagion: Empirical Evidence [J]. Bank of Canada Working paper, No.1, 2003.
    113. Schoenmaker, D. Contagion Risk in Banking [J]. Working paper, dp239, Financial Markets Group Research Centre at LSE, 1996.
    114. Serrano, M.A., and M. Boguna. Topology of the World Trade Web [J]. Phys. Rev. E, 2003, 68(R), 015101.
    115. Sheehan B. Myth and Reality in Chinese Financial Cliques in 1936 [J]. Enterprise & Society: The International Journal of Business History, 2005, 6, 3: 452-491.
    116. Sheldon, G., and M. Maurer. Interbank Lending and Systemic Risk: An Empirical Analysis for Switzerland [J]. Swiss Journal of Economics and Statistics, 1998, 134(4): 685-704.
    117. Soramaki K., M. L. Bech. Systemic Risk in a Netting System Revisited [J]. Federal Reserve Bank of New York Working Paper, 2004.
    118. Souma, W., Y. Fujiwara and H. Aoyama. Complex Networks and Economics [J]. Physica A, 2003, 324: 396-401.
    119. Strogatz, S.H. Exploring Complex Networks [J]. Nature, 2001, 410: 268-276.
    120. Summer, M. Banking Regulation and Systemic Risk [J]. Open Economics Review, 2003, 43-70.
    121. Tanaka R.,Scale-Rich Metabolic Networks[J], Phys. Rev. Lett. 2005, 94, 168101.
    122. Thurner, S. Network Dependence in Risk Trading Games: A Banking Regulation Model [J]. AIP Conf. Proc., 2003, 661(1): 28-32.
    123. Thurner, S., R. Hanel and S. Pichler. Risk Trading, Network Topology, and Banking Regulation [J]. Quantitative Finance, 2003, 3: 306-319.
    124. Upper, C., and A. Worms. Estimating bilateral exposures in the German Interbank Market: Is there a Danger of Contagion? [J]. Deutsche Bundesbank Discussion paper, 09/02, 2002.
    125. Upper, C., and A. Worms. Estimating bilateral exposures in the German Interbank Market: Isthere a Danger of Contagion? [J]. European Economic Review, 2004, 48: 827-849.
    126. Wan, Y.S., and Z. Chen. Scale-Free Behavior in a Novel Weighted Stock Network [J]. Journal of Southwest Jiaotong University, accepted, 2006.
    127. Wan, Y.S., and Z. Chen. Modeling the Two-Power-law Degree Distribution of Banking Networks [J]. Dynamics of Continuous, Discrete & Impulsive Systems, 2006, 13(3-4): 441-449.
    128. Watts, D.J., P.S. Dodds M.E. Newman. Identity and Search in Social Networks [J]. Science, 2002, 296: 1302-1305.
    129. Watts, D.J., and S.H. Strogatz. Collective Dynamics of Small-World Networks [J], Nature, 1998, 393: 440-442.
    130. Wells, S. UK Interbank Exposures: Systemic Risk Implications [R]. Bank of England Financial Stability Review, 2002, 175-182.
    131. Wells, S. Financial Interlinkages in the United Kindom’s Interbank Market and the Risk of Contagion [J]. Bank of England Working paper, No.230, 2004.
    132. Worms, A. Interbank Relationships and the Credit Channel in Germany [J]. Empirica, 2003, 30: 179-198.
    133. Xie D. Analysis of the Development of China’s Money Market [J]. China & World Economy, 2002, 1: 29-37.
    134. 包全永. 银行系统性风险的传染模型研究 [J]. 金融研究, 2005, 8: 72-84.
    135. 车宏安, 顾基发. 无标度网络及其系统科学意义 [J]. 系统工程理论与实践, 2004, 4: 11-16.
    136. 方锦清, 汪小帆,刘曾荣. 略论复杂性问题和非线性复杂网络系统的研究 [J]. 科技导报,2004,2: 9-12.
    137. 范小云. 中国银行间市场双边传染风险估测及系统性特征分析 [R]. 中国金融学年会主题发言论文,2005.
    138. 范小云, 曹元涛. 银行系统性风险测度最新研究比较及其在中国的应用前景 [J]. 经济学动态,2006, 1: 55-58.
    139. 高洪民. 资产负债表的直接传染——一种银行与企业信用链上的信贷冲击乘数效应 [J]. 财经研究, 2005, 11: 5-16.
    140. 蒋序怀, 吴富佳. 当前资本市场的风险传导机制——基于传染效应的实证分析 [J]. 金融论坛,2006, 2: 16-24.
    141. 李宗怡,李玉海. 我国银行同业拆借市场“传染”风险的实证研究 [J]. 财贸研究, 2005, 6: 51-58.
    142. 清泷信宏, 约翰·穆尔. 平衡表的传染效应 [J]. 比较, 2003, 5: 109-116.
    143. 谭跃进, 吴俊. 网络结构熵及其在非标度网络中的应用 [J]. 系统工程理论与实践,2004,6: 1-3.
    144. 吴清泉, 王锦云. 资本市场风险传染效应分析 [J]. 财政金融,2005, 10: 20-22.
    145. 吴金闪,狄增如. 从统计物理学看复杂网络研究 [J]. 物理学进展,2004,24(1): 18-46.
    146. 谢平,柴洪峰等. 我国银行间市场的未来发展和交易场所组织模式研究 [J],金融研究,2002, 5: 1-15.
    147. 许国志. 系统科学 [M]. 上海:上海科技教育出版社, 2000.
    148. 许国志. 系统科学与工程研究 [M]. 上海:上海科技教育出版社, 2000.
    149. 陈忠,金炜,章琪. 复杂性的探索 [M]. 安徽:安徽教育出版社, 2002.

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