基于信用风险和利率风险的资产组合优化模型研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
资产负债管理能力是现代商业银行的基本能力,其核心是价值创造和风险控制。商业银行资产负债组合优化是现代商业银行信贷管理框架中的核心内容,它对于保持银行资产“三性”的最佳组合、优化配置资源、提高银行的生存能力和竞争能力,具有重要的现实意义。
     本论文共分五章,第一章绪论阐述了论文的选题依据、相关研究进展、研究方法和研究内容;第二章建立了基于信用风险管理的贷款组合优化模型;第三章探讨基于利率风险管理的资产负债组合优化模型;第四章是基于信用风险久期免疫的资产负债组合优化模型;第五章结论与展望。论文的主要研究成果如下:
     (1)建立了基于看跌期权组合值最大化的银行资产优化模型
     通过卖出看跌期权的组合价值来客观地反映企业价值影响贷款清偿能力的本质属性,提出了银行债权价值与卖出看跌期权等价原理,建立了基于看跌期权组合价值最大化的银行资产优化模型,在避免银行重大损失的情况下追求收益最大,解决了规避银行巨大贷款风险的重大问题,开辟了资产优化配置研究新思路;通过看跌期权这种银行债权组合价值最大的一个目标函数既反映了贷款收益、又反映了贷款风险。既解决了单一目标不全面反映银行经营目标、又解决了多目标决策时不同目标的权重分配缺乏客观性的问题。
     (2)建立了基于风险价值约束的贷款组合效用最大化优化模型
     用风险价值VaR来控制风险,根据在贷款组合有效边界上银行效用最大化的目标分配各项贷款,建立了基于风险价值约束的贷款组合效用最大化决策模型。在控制贷款组合风险价值VaR的前提下实现贷款组合效用最大化,改变了现有研究在考虑效用最大时忽略风险控制的问题,解决了在风险控制的前提下实现效用最大的优化问题;通过贷款组合效用最大配给贷款符合贷款优化的目的,体现了资产组合优化是使投资者期望效用最大化的决策这一本质的属性,改变了现有研究大多在主观给定风险或主观给定收益率水平的前提下确定最优贷款组合的现状,消除了贷款分配过程中的主观因素,解决了决策模型与决策目的不相一致的问题。
     (3)建立了基于方向久期利率风险免疫的资产负债组合优化模型
     提出了方向久期免疫组合优化原理,以方向久期缺口免疫为条件,以控制贷款组合的利率风险为目标,建立了基于方向久期免疫的资产负债组合优化模型。通过不同时期即期收益率对现金流的贴现,以某一特定时段的利率变化量除以全部时段利率变化量的均值作为系数,对反映时间权重的未来现金流再进行加权,科学地反映利率波动对现金流平均回收期的影响。
     (4)建立了基于现金流离散度缺口免疫的资产负债组合优化模型
     本模型引入现金流离散度对收益率曲线非平行移动带来的利率风险进行免疫,提出了现金流离散度M~A零缺口免疫组合优化原理,建立了基于现金流离散度M~A缺口免疫的银行资产负债组合优化模型。通过现金流离散度的零缺口免疫匹配银行的资产与负债、控制了利率期限结构非平行移动带来的利率风险,避免了传统久期免疫不能控制的利率期限结构非平行移动带来的利率风险的弊端;通过不同时段的远期收益率来贴现资产和负债的现金流、使现金流离散度的计算更加准确,反映了不同时期收益率变化对各期现金流的影响,提高了现金流离散度的计算精度,改变了传统久期免疫用恒定的名义利率贴现现金流的做法。
     (5)建立了基于信用风险久期免疫的资产负债组合优化模型
     通过运用看跌期权公式建立了贴现率与违约风险的函数关系,构造了信用风险久期免疫条件,建立了基于信用风险久期免疫组合优化模型,规避了利率风险和信用风险对所有者权益的影响。通过看跌期权公式建立了贴现率与违约风险的函数关系,揭示了违约风险对贴现率的影响。反映违约风险的贴现率替代市场基准利率表述信用久期函数,揭示了信用风险对久期的影响。这就改变了现有研究人为的认为久期与信用风险无关的现状。
     本文立足金融领域的前沿课题、创建符合银行运作规律的资产负债管理决策理论,为银行资产负债管理创建新理论、建立新模型,促进银行资产负债管理理论体系的完善。
Asset-Liability management is the basic ability of modern commercial banks, the core of which is to create value and control risk. Asset-Liability combinatorial optimization of commercial banks is the core content in the framework of a modern commercial bank management. It is of great realistic significance to maintain the best combination of "three characters" of the bank's assets, optimize allocation of resources, enhance the bank's viability and competitiveness.
     This paper is divided into five chapters. The first chapter describes the basis of selection, process, methods and contents of related research in the paper. The second chapter builds the loan portfolio optimization model based on credit risk management. The third chapter discusses the Asset-Liability portfolio optimization model based on the interest rate risk. The fourth chapter discusses optimization model of Asset-Liability portfolio based on credit risk duration immunization of interest rate risk. The fifth Chapter is the Conclusion and Outlook. The main results of the thesis are as follows:
     (1) It sets up distribution model of asset-liability-management based on the value maximization of Short Puts Portfolio.
     This paper treats the enterprise loan as a loan portfolio and optimize this load portfolio by maximize the portfolio value, thus the loan's time value and inner value can be same reflected and successfully confirm the objective of loan portfolio optimization. It is a pursuit of the biggest gains based on avoiding heavy losses. In order to open up a new thought of assets' optimal allocation and address the major issue of avoid the risk of bank loans, it sets up distribution model of asset-liability-management based on the value maximization of Short Puts Portfolio. Using the portfolio value maximum of bank's assets as objective function, both reflect the double goal of income maximization and risk minimization, enable a more accurate distribution policy of the loan portfolio, and also resolve the overall measurement limitation of single objective function on income and risk.
     (2) It sets up optimization model of loan's portfolio utility maximization based on the yield of VaR.
     Optimization of asset portfolio is the decision that maximizes the expected utility of investors. This paper controls the risk through Value at Risk (VaR), distributes loans according to the maximization of banks' utility on the efficient boundary of the loan's portfolio, and establishes the decision model for the maximization of the utility of the loan's portfolio based on the restriction of VaR. This paper maximizes the utility of loan's portfolio with the control of its VaR, which can solve the problems of existing studies that the control of risk is neglected while maximal utility is considered, and that the utility can not be optimized under the control of VaR. It optimizes loans to distribute them through the maximization of the utility of loan's portfolio and represents one nature of the Optimization of Asset Portfolio that maximizes the expected utility of investors, changes the situation among most existing studies based on subjective risk and yield, removes the subjective factors in the distribution of loans, and solves the problem between the decision model and purpose.
     (3) It sets up optimization model of Asset-Liability portfolio based on directional duration immunization of interest rate risk.
     The paper sets up optimization model of asset-liability portfolio based on immunization of interest rate risk by taking directional duration gap for condition, and loan portfolio's interest rate risk controlling for aim. It uses directional duration portfolio optimization condition to control interest rate risk of loan portfolio. Discounting cash-flow by different spot interest rate in different period of time which changes the unreasonable condition, it discounts cash-flow by the nominal rate in current research. It reflects the influence of different spot interest rate in different period of time on the average pay-off period.
     (4) It sets up optimization model of Asset-Liability portfolio based on non-parallel shift interest rate risk control.
     Introducing M-Absolute to immune the interest rate risk caused by the non-parallel shift of yield curve, this paper establishes the principle and optimization model of Asset-Liability portfolio based on immunization of non-parallel-shift interest rate risk. This model matches the assets and liabilities of commercial bank by M-Absolute zero-gap immunization, which controls the interest rate risk caused by the non-parallel shift of interest term structure. Discounting cash-flow of the assets and liabilities by different forward interest rate, the calculation of the M-Absolute is more accurate, which reflects the various yield point changement, improves the accuracy of the calculation of the M-Absolute and changes the discounted methods that used invariable nominalinterest rate.
     (5) It sets up optimization model of Asset-Liability portfolio based on credit risk duration immunization of interest rate risk.
     This paper which use the interest rate adjusted by risk premium instead of risk-free rate, sets up optimization model of asset-liability portfolio based on immunity conditions of credit risk, and loan portfolio's interest rate risk controlling for aim. It can avoid loss of owners' equity caused by interest risk and credit risk. Application of put option to establish the function relationship between deflaut risk and discount rate discover effect of deflaut risk on discount rate. The discount rate which reflects deflaut risk is used to express function of credit risk duration. It reflects the influence of deflaut risk on duration. It can change the current paper assumption that deflaut risk not related to duration.
     This paper bases on financial field frontier, establishes decision theory and decision methods of Asset-Liability management. It establishes new theory and sets up new models for the eommereial bank, thus results in promoting the perfection of the oretieal system on Asset-Liability management.
引文
[1]叶望春,夏清华.银行危机对商业银行资产配置的启示[J].世界经济,2001,(9):69-72.
    [2]2007年商业银行不良贷款情况表,中国银行业监督管理委员会http://www.cbrc.gov.cn/chinese/home/jsp/docView.jsp?docID=20070516A4DD51DB0062F0CBF F883AB8A21E4800
    [3]杨宜,房艳.商业银行业务管理[M].北京:机械工业出版社,2004:216-220.
    [4]Peter,S.R.Commercial Bank Management[M].5th ed.,New York:The McGraw-Hill Companies,Inc.2002:199-200.
    [5]赵天荣.存续期缺口模型在资产负债管理中的应用.财经科学[J].2003,增刊:235-237.
    [6]Markowitz H.Portfolio selection:efficient diver-sification of investments[J].The Journal of Finance,1952,7(1):77-91.
    [7]Morgan.J.B.and T.L.Ggollinger.Calculation of an fficient frontier for a Commercial Loan Portfolio[J].Journal of Portfolio Management(winter),1993.
    [8]洪忠诚.商业银行风险管理中的贷款组合分配模型研究[D].大连:大连理工大学,2006:4-8.
    [9]Sheedy,E,Trevor,R and Wood,J.Asset-Allocation Decisions When Risk is Changing[J].Journal of Financial Research,1999,22(3):301-315.
    [10]迟国泰,姜大治,奚扬,林建华.基于VaR收益约束的贷款组合优化决策模型[J].中国管理科学,2002,10(6):1-7.
    [11]陈铁英,张忠桢.自融资均值方差投资组合模型的旋转算法[J].系统工程理论与实践,2004,(6):98-103.
    [12]李菁,王宗军,王治.商业银行信贷资产组合优化研究[J].统计与决策,2005,(11)20-22.
    [13]张萍.均值-方差-峰度资产组合优化模型基于对峰度风险的考虑[J].科学技术与工程,2008,8(1):16-20.
    [14]Li,D.,and Ng,Wan Lung.Optimal dynamic portfolio selection:Multiperiod mean-variance formulation[J].Mathematical Finance,2000,10(3):387-406.
    [15]庄新田,黄小原.银行资产负债管理的模型及优化[J].系统工程理论方法应用,2001,10(2):167-171.
    [16]Tokat Y,Rachev S T,Schwartz E S.The Stable non-Gaussian asset allocation:a comparison with the classical Gaussian approach[J].Journal of Economic Dynamics & Control,2003,27(6):937-969.
    [17]袁乐平,黄博文.基于VaR约束的商业银行资产负债组合配给模型探讨[J].中南大学学报(社会科学版),2005,11(2):217-221.
    [18]迟国泰,郑杏果,许文.基于Monte Carlo模拟和VaR约束的银行资产组合优化模型[J].系统工程理论与实践,2006,(7):66-75.
    [19]迟国泰,董贺超,孙秀艳.基于多期动态优化的银行资产组合决策模型[J].系统工程理论与实践,2007,(2):1-16.
    [20]Altman E I.Corporate bond and commercial loan portfolio analysis[Z],Working Papers-97-12,New York University Salomon Brother Center,1997.
    [21]Caouette J B.Managing credit risk:The Next Great Financial Challenge[M].New York:John Wiley & Sons,Inc.,1998:274-280.
    [22]迟国泰,秦学志,朱战宇.基于单位风险收益最大原则的贷款组和优化决策模型[J].控制与决策,2000,15(4):469-472.
    [23]郑锦亚,迟国泰.基于差异系数σ/μ的最优投资组合方法[J].中国管理科学,2001,9(1):1-5.
    [24]张金清,基于单位收益风险的投资决策模型与分析[J].湖南文理学院学报(自然科学版),2004,16(2):66-70.
    [25]王尚户,张崇岐.基于均值-AVaR的投资组合均衡分析[J].广州大学学报(自然科学版),2007,6(6):11-13.
    [26]秦学志,迟国泰.多准则多目标信贷策略的动态规划方法[J].中国管理科学,2000,8(专辑):18-24.
    [27]郭战琴,周宗放.基于VaR约束的商业银行贷款组合多目标决策[J].系统工程理论方法应用,2005,14(2):149-152.
    [28]迟国泰,王化增,杨德.基于信用迁移全部贷款组合优化下的新增单笔贷款决策模型[J].系统管理学报,2008,17(1):1-7.
    [29]Steinbach M C,Markowitz H.Revisited:mean-variance models in financial portfolio analysis[J].Siam Review,2001(43):31-85.
    [30]王春峰,屠新曙,厉斌.效用函数意义下投资组合有效选择问题的研究[J].中国管理科学,2002,10(2):15-19.
    [31]Cohen MH,Natoli V D.Risk and utility in portfolio optimization[J].Physica A.2003,324(1-2):81-88.
    [32]张鹏,张忠桢,岳超源.基于效用最大化的投资组合旋转算法研究[J].财经研究,2005,31(12):116-125.
    [33]初叶萍,张鹏.无风险资产的投资组合效用最大化的模型研究[J].武汉理工大学学报(信息与管理工程版),2006,28(8):118-121.
    [34]朱微亮,刘海龙.稳健的动态资产组合模型研究[J].中国管理科学,2007,15(3):20-24.
    [35]Jarrow,R,D.Lando and S.Turnbull.A Markov Model for the Term Structure of Credit Risk Spreads.Review of Financial Studies,1997,10:481-523.
    [36]迟国泰,奚扬,姜大治,林建华.基于VaR约束的银行资产负债管理优化模型[J].大连理工大学学报,2002,11:750-758.
    [37]蔡海燕.商业银行信用风险管理模型应用探讨[J].经济师,2008,(7):198-199.
    [38]陈旭鸣.现代信用风险管理模型发展研究[J].统计与决策,2008,(9):186-188.
    [39]KMV Corporation,1995.Introduction to Credit Monitor,Portfolio Manager,and Private Model,http://www.kmv.com/.
    [40]韩立岩,郑承利.基于模糊随机方法的公司违约风险预测研究[J].国际金融研究,2002,8:48-53.
    [41]赵跃琼,严广乐.KMV模型在银行贷款定价中的应用[J].上海理工大学学报,2006,28(1):23-26.
    [42]李磊宁,张凯.KMV模型的修正及在我国上市公司信用风险度量中的应用[J].首都经贸大学学报,2007,(4):44-48.
    [43]Michael B.Gordy.A comparative anatomy of credit risk models.Journal of banking & Finance 24(2000):119-149.
    [44]张亚涛.现代信用风险度量模型的对比分析[J].山西财经大学学报.2002,24(6):107-108.
    [45]张海明,马永开.基于CreditRisk+的银行全面资产负债管理目标规划模型研究[J].电子科技大学学报,2006,3:29-33.
    [46]黄丰俊,刘江涛.商业银行授信资产组合管理研究[J].国际金融研究,2007,(6):23-31.
    [47]Wilson,T.,Portfolio credit risk I.Risk 10(9),September,1987.
    [48]G.O.Bierwag,GeorgeG.Kaufman,andChulsoonKhang.Duration and Bond Portfolio Analysis:An Overview[J].Journal of Financial & Quantitative Analysis,1978,(11):671.
    [49]Booth G,Bessler W,Foote W G.Managing interest rate risk in banking institutions[J].European Journal of Operational Research,1989,41:302-313.
    [50]Duan J,Sealey C.W.Managing bank' s duration gaps when interest rates are stochastic and equity has limited liability[J].International Review of Economics and Finance,1999,(8):253-265.
    [51]Moreno M.Risk Management under a Two-Factor Model of the Term Structure of Interest Rates.http://econpapers.hhs.se/paper/upfupfsbf/254.htm,2003-03-10.
    [52]迟国泰,许文,王化增.兼控利率风险和流动性风险的资产负债组合优化模型[J].控制与决策,2006,21(12):1407-1416.
    [53]刘湘云,唐娜.商业银行利率风险:基于久期缺口的免疫策略及实证分析[J].南京航空航天大学学报(社会科学版),2006,8(3):38-41.
    [54]朱毅峰,孙亚南,杨崛.商业银行资产负债管理——两类缺口模型的评介[J].生产力研究,2008,(7):42-43.
    [55]夏小鸥.金融工程中的久期再修正[J].金融教学与研究,1999,(5):12-16.
    [56]左卫丰.久期模型比较分析及其应用研究[D].长沙:中南大学,2005.
    [57]张姣.利率风险管理的重要免疫工具—持续期模型[D].大连:东北财经大学,2005.
    [58]Deshmukh,Greenbaum,Kanatas.Interest Rate Uncertainty and the Financial Intermediary's Choice of Exposure[J].The Journal of Finance,1983,(3):141-147.
    [59]郑延平,东文.商业银行利率风险分析[J].南方金融,2001,(7):48-51.
    [60]Gady Jacoby.A Duration Model for Defaultable Bonds.The Journal of Financial Research,2003,1(1):129-146.
    [61]邓黎阳,孙刚.商业银行利率风险测度方法的现实选择—Fisher-Weil久期模型的应用[J].国际金融研究,2005,(12):4-11.
    [62]邓超,左卫丰.久期模型及其最新拓展[J].湖南商学院学报,2005,12(4):68-71.
    [63]杨飞.久期技术与基于隐含期权的商业银行利率风险管理[J].科技与管理,2006,(6):104-106.
    [64]王春峰,张伟.基于久期缺口模型的隐含期权利率风险管理[J].系统工程理论方法应用,2001,10(4):269-275.
    [65]罗大伟,万迪昉.有隐含期权的银行资产负债表的利率风险控制[J].系统工程理论与实践,2002,(8):55-60.
    [66]Davidson.Why Effective Duration Impacts Interest-Rate Risk[J].Community Banker,2002,(4):36-37.
    [67]李丹,迟国泰,孙秀艳.基于期权调整持续期的银行资产负债组合优化模型[J].价值工程,2006,(11):151-152.
    [68]卜壮志,徐成贤.商业银行利率风险管理方法的比较研究[J].统计与决策,2007,(22):113-116.
    [69]夏和平,周茂彬,王小明.存货款业务中的隐含期权对我国商业银行利率风险的影响[J].金融研究,2007,(9):138-150.
    [70]屠新曙,王春峰,巴曙松.投资组合效用问题的研究[J].数量经济技术经济研究,2002,(5):37-40.
    [71]Walk H,Yakowitz S.Iterative Nonparametric Estimation of A Log-optimal Portfolic Selection Function[J].IEEE Transactions on Information Theory,2002,48(1):324-335.
    [72]谢云山.信用风险和利率风险相关性分析—利率市场化下商业银行的新型风险管理模式[J].国际金融研究,2004,(10):51-60.
    [73]李栋.我国商业银行信用风险存在的问题及成因.商业经济,2009(1):75-76.
    [74]程鹏,吴冲锋,李为冰.信用风险度量和管理方法研究[J].管理工程学报,2002,16(1):70-73.
    [75]Hull,J..Options,Futures,and Other Derivatives[M]Prentice-Hall,1997.
    [76]盛骤,谢式千等.概率论与数理统计[M].北京:高等教育出版社,2001,160-174.
    [77]郑龙欣.VaR方法在我国商业银行风险管理中的应用[J].金融经济,2008,14:81-82.
    [78]王春峰.金融市场风险管理[M].天津:天津大学出版社,2001.
    [79]Markowitz,H.portfolio Selection:Efficient Diversification of Investments[J].New York:John Wilev&Sons,Inc.1959.
    [80]刘次华,万建平.概率论与数理统计[M].北京:高等教育出版社,2003,137-141.
    [81]Mark Kritzman.About Utility[J].Financial Analysts Journal,1992,48(3):17-20.
    [82]俞乔,邢晓林,曲和磊.商业银行管理学[M].上海:上海人民出版社,1998:192-195,573-603.
    [83]Puelz A V.Aseest and Liablitily Mangement:A stochasic Moedl for Portfolio Proceedings of the 1997 IEEE/IAFE Conference on Computational Intelligence for Ficance Engineering.NJ,1997,36-42.
    [84]Robert R.Reitano.Non-Parallel Yield Curve Shifts and durational leverage.Journal of Portfolio Mangement,1990,16(4):62-67.
    [85]Robert R.Reitano.Non-Parallel Yield Curve Shifts and Immunization.The Journal Portfolio Mangement,1992,18(3):36-43.
    [86]迟国泰,徐琤,李延喜.银行资产负债管理中的资产分配模型[J].大连理工大学学报(自然科学版),2001,41(4):501-504.
    [87]傅强,蒋安玲.国债即期利率期限结构研究[J].金融与经济,2005,(3):57-59.
    [88]上海交易所,国债收盘价,http://www.sse.com.cn,2006-10-13.
    [89]薛一飞,张维,刘豹.我国债券投资中一种利率风险最小化模型的分析[J].系统工程理论方法应用.1999,8(1):1-10.
    [90]Sanjay K.Nawalkha,Donald R.Chambers.An Improved Immunization Strategy:M-Absolute[J].Financial Analysis Journal,1996,(9):69-75.
    [91]黄智猛,吴冲锋.债券利率风险的一种度量方法[J].系统工程,2000,18(1):34-37.
    [92]邵斌,徐蓉,陈芳菲.远期利率与国债收益率曲线的构造[J].投资学评论,2004,(2):39-51.
    [93]秦江波,于冬梅.中国商业银行利率风险的理论与实证[J].科技与管理,2008,(3):58-60.
    [94]Chance,Don M.Default risk and duration of Zero coupon Bonds[J].Journal of Finance.1990,41(1):265-274.
    [95]Merton R.On the Pricing of Corporation Debt:the Risk Structure of Interest Rates[J].Journal of Finance.1994,28:449-470.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700