基于“四维久期”利率风险免疫的资产负债组合优化模型
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摘要
利率风险管理是银行资产负债管理中的核心内容。以银行月利息收益最大为目标函数,以水平、斜率、曲率和峰度4个维度的零久期缺口为约束条件,构建商业银行资产负债组合优化模型。将反映收益率曲线水平因子、斜率因子、曲率因子和峰度因子4个维度变化的Svensson模型参数引入经典的Nelson-Siege久期模型,建立"四维久期"模型,从4个维度更加准确地衡量利率风险。不但可以反映Nelson-Siege久期的水平因子、斜率因子和曲率因子,而且还反映了峰度因子。以"四维久期"的利率风险免疫条件为约束,以商业银行利息收益最大为目标函数,建立控制利率非移动风险的资产负债组合优化模型,确保在利率发生变化时,银行的净资产不受损失。
Interest rate risk management is the core content in bank assets and liabilities management. Taking the maximum monthly interest income of the bank as the objective function, with the zero-period gaps of the four dimensional duration: horizontal, slope, curvature, and kurtosis as the constraints, the asset-liability portfolio optimization model of commercial banks was constructed. The parameters of the Svensson model, which reflect the four dimensions of the yield curve, the slope factor, the curvature factor, and the kurtosis factor, were introduced into the classic Nelson-Siege duration model, which can measure the interest rate risk more accurately from four dimensions, and can ensure that the net assets of commercial banks are not lost when interest rates changes.
Interest rate risk management is the core content in bank assets and liabilities management. Taking the maximum monthly interest income of the bank as the objective function, with the zero-period gaps of the four dimensional duration: horizontal, slope, curvature, and kurtosis as the constraints, the asset-liability portfolio optimization model of commercial banks was constructed. The parameters of the Svensson model, which reflect the four dimensions of the yield curve, the slope factor, the curvature factor, and the kurtosis factor, were introduced into the classic Nelson-Siege duration model, which can measure the interest rate risk more accurately from four dimensions, and can ensure that the net assets of commercial banks are not lost when interest rates changes.
引文
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[15] 张远为,林江鹏.一种计算债券久期和凸度的简单方法[J].西南金融, 2014(1): 12-15.
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[22] 王克明,梁戍. 基于利率期限结构的随机久期与凸度模型构建及应用[J].统计与决策, 2010(21): 158-160.
[23] 殷樱,宋良荣,徐春晓. 基于随机久期的商业银行价值优化研究[J].财务与金融, 2013(1): 1-4.
[24] 李鹏程,李晶晶,杨宝臣. 随机久期利率风险免疫策略研究[J].经济与管理研究, 2014(8): 50-54.
[25] Svensson L E O. Estimating forward interest rates with the extended Nelson & Siegel method[J]. Quarterly Review, 1994(1): 13-26.
[26] 杨婉茜,成力为. 基于Nelson-Siegel模型控制利率风险的资产负债组合优化模型[J].系统工程, 2014, 32(1): 12-20.
[27] 刘艳萍,巩玉芳,迟国泰. 基于利率非平行移动风险控制的资产负债组合优化模型[J].管理学报, 2009, 6(9): 1215-1225.
[28] 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(9): 1407-1416.
[29] 锐思数据库[EB/OL]. http://www2.resset.cn/product/.
[30] 陈映洲,张健. 基于动态Svensson模型的国债利率期限结构实证分析[J].统计与信息论坛, 2015, 30(1): 38-43.
[31] 迟国泰,闫达文. 基于VaR控制预留缺口的资产负债管理优化模型[J].管理工程学报, 2011, 25(1): 123-132.
[2] Diebold F X, Li C. Forecasting the term structure of government bond yields[J]. Journal of Econometrics, 2006, 130(2): 337-364.
[3] 张蕊,王春峰,房振明,等. 上交所国债市场流动性溢价研究——基于4因子仿射利率期限结构模型[J]. 系统管理学报, 2009, 18(5): 481-486.
[4] 贾德奎. 货币政策透明度与政策有效性:基于利率期限结构预期理论的检验[J]. 系统管理学报, 2010, 19(5): 503-508.
[5] Macaulay F R. Some theoretical problems suggested by the movement of interest rates, bonds, yields, and stock prices research[R]. Columbia University Press, 1938: 44-53.
[6] Samuelson P A. The effect of interest rate increases on the banking system[J]. American Economic Review, 1945 (1): 6-27.
[7] Fisher L, Weil R L. Coping with the risk of interest-rate fluctuations: Return to bond holders from na?ve and optimal strategies[J]. Journal of Business, 1971, 44(1): 408-431.
[8] 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(1): 38-41.
[9] 于鑫,霍春光.基于久期模型的债券免疫策略分析[J].商, 2012(8): 55.
[10] 孔婷婷,张杨.基于久期缺口模型的商业银行利率风险免疫策略及实证分析[J].西安工业大学学报, 2013, 33(8): 922-929.
[11] 刘韵婷,曾秀文,黄嘉英.利率市场化下商业银行的利率风险研究[J].经济研究导刊, 2014(11): 193-196.
[12] 施恬.商业银行利率风险管理中久期缺口测算及其防御策略——基于中国股份制商业银行的实证分析[J].上海金融, 2014(2): 103-106.
[13] Fabozzi F J. Bond market, analysis and strategies[M]. Publisher: Prentice Hall, 1993.
[14] 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(3): 104-106.
[15] 张远为,林江鹏.一种计算债券久期和凸度的简单方法[J].西南金融, 2014(1): 12-15.
[16] 唐恩林.隐含期权对商业银行久期匹配策略的影响分析[J].安徽农业大学学报(社会科学版), 2014, 23(1): 54-59.
[17] Reitano R R. Non-parallel yield curve shifts and spread leverage[J]. Journal of Portfolio Management, 1991: 82-87.
[18] 吴灏文, 迟国泰. 基于方向久期与凸度免疫的资产负债优化模型[J].系统工程学报, 2012, 27(1): 506-512.
[19] Bierwag G O, Kaufman G G. Coping with the risk of interest-rate fluctuation: A note[J]. Journal of Business, 1977, 50(1): 364-370.
[20] Vasicek O. An equilibrium characterization of the term structure[J]. Journal of Financial Economics, 1977, 5(1): 177-188.
[21] Rakesh B, Prasad N, Jacky S. Dynamic gap transformations: Are banks asset-transformer or both?[J]. The Quarterly Review of Economics and Finance, 2006(43): 36-52.
[22] 王克明,梁戍. 基于利率期限结构的随机久期与凸度模型构建及应用[J].统计与决策, 2010(21): 158-160.
[23] 殷樱,宋良荣,徐春晓. 基于随机久期的商业银行价值优化研究[J].财务与金融, 2013(1): 1-4.
[24] 李鹏程,李晶晶,杨宝臣. 随机久期利率风险免疫策略研究[J].经济与管理研究, 2014(8): 50-54.
[25] Svensson L E O. Estimating forward interest rates with the extended Nelson & Siegel method[J]. Quarterly Review, 1994(1): 13-26.
[26] 杨婉茜,成力为. 基于Nelson-Siegel模型控制利率风险的资产负债组合优化模型[J].系统工程, 2014, 32(1): 12-20.
[27] 刘艳萍,巩玉芳,迟国泰. 基于利率非平行移动风险控制的资产负债组合优化模型[J].管理学报, 2009, 6(9): 1215-1225.
[28] 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(9): 1407-1416.
[29] 锐思数据库[EB/OL]. http://www2.resset.cn/product/.
[30] 陈映洲,张健. 基于动态Svensson模型的国债利率期限结构实证分析[J].统计与信息论坛, 2015, 30(1): 38-43.
[31] 迟国泰,闫达文. 基于VaR控制预留缺口的资产负债管理优化模型[J].管理工程学报, 2011, 25(1): 123-132.