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当前位置:首页 > 金融/证券 > 金融资料 > 商业银行流动性风险集成式评价模型及实现研究
华中科技大学硕士学位论文商业银行流动性风险集成式评价模型及实现研究姓名:吴金星申请学位级别:硕士专业:企业管理指导教师:王宗军20040428IGM11BPBPIIAbstractDevelopmentwiththemixedbusinessoffinancialindustryandentranceofforeignbanks,thefinancialindustryofChinaisfacingtheausterecompetingsituation.InordertoadapttothesituationthebankindustryasthemainforceofthefinancialindustryofChinamuststrengthentheconsciousnessofriskmanagement,improvethelevelofriskmanagementandupgradethecomprehensivecompetitiveness.Therefore,astheeffectivemeansofupgradingthecomprehensivecompetitiveness,theliquidityriskmanagementbecomesmoreandmoreimportantincommercialbanks’operationmanagement.InordertoresearchandevaluatetheliquidityriskofcommercialbanksinChina,thispaperlucubratedtheliquidityriskstepbystep.Themaincontentsofresearchinthispaperarethefollowing:Firstlythispaperexpoundedtheconceptsandcharactersofriskandbankrisk.Thenitbroughtforwardtheconceptandcharactersoftheliquidityriskandanalyzedtheobjectivesandsignificanceofliquidityriskmanagementespeciallyintheelectricandnetworkedcondition.Secondlyitreviewedthedomesticandforeigntheoriesofliquidityriskmanagement,analyzingtheirtimesbackgroundandtheadvantagesandshortcomingsofeachtheory.Nextitsummedupvariousmethodsofliquidityriskmanagement,providingthebasicforestablishingtheintegratedevaluationmodelforliquidityriskmanagement.ThirdlyitqualitativelyanalyzedtheliquidityriskmanagementsituationanditscausesincommercialbanksofChinaandbroughtforwardthereconstituteconceiveofliquidityriskmanagementaccordingtoliquidityriskmanagementpracticeoverseas.Fourthlyitdesignedthestructureoftheliquidityriskmanagementsystemandestablishedtwoindexessystems:oneformonitoringtheliquiditydemandandsupplyandtheotherforevaluatingtheassetallocation,toestablishtheintegratedevaluationmodelforliquidityriskmanagementbasedonGM(1,1)andBack-PropagationNeuralNetworkbyutilizingtheconceptsandcharactersofliquidityriskandcatchingtheessenceofliquidityriskmanagementliquiditygapmanagementandassetallocation.Fifthlyitcarriedouttheempiricalproof-testtoverifytheeffectoftheintegratedevaluationmodelforliquidityriskmanagementandtheempiricalresultsindicatedthattheintegratedevaluationmodelhadIIIhigherveracityandreliabilityinmorehigherconfidentiallevel.Thenitputforwardtheimprovedadvicefortheevaluationmodelforassetallocation.Finallyitreviewedthetheoriesandmethodsofliquidityriskmanagement,analyzedtheadvantagesandshortcomingsoftheintegratedevaluationmodelandbroughtforwardtheimprovedadvicesforthemodel.Anyenterpriseneedsliquidity,buttheliquidityisthefrailestincommercialbanks.Anyenterpriseneedscredit,butthecreditisthemostessentialtocommercialbanks.Therefore,itisthemostsignificantthatstrengtheningtheliquidityriskmanagementandimprovingtheirowncomprehensivecompetitivenessforcommercialbanksinChinatoadaptthenewcompetitivesituationandmarchtowardtheinternationalization.KeyWords:CommercialBanksLiquidityRiskIntegratedEvaluationModelB-PNeuralNetwork111.11.1.11895l921[1]M000[2](1)(2)(3)1.1.2220301.2[3][4][5][6][7]3[8][9]1.3[10]JameTubin1[11][12]2()3(Sinkey)4),,,(LIQSOENWfC=1-1CNWSOEIQL[11][13]1.4WTO[14][15]1.4.11523[16]1.4.2121[17]ATMPOS62[10]3[10]72[18][19]2.12060AssetManagementTheory2.1.1TheCommercialLoanTheoryTheRealBillsDoctrine812342.1.2TheShiftabilityTheory1918H.G.Moulton[20][21]912()32.1.31949VTheAnticipatedIncomeTheory102.1.42070TheSuperCurrency-SupplyTheory2.1.5TheAssetStructureTheory1()12[22]1132.22050602.2.1123Q1242.2.2TheBankBondTheory2.2.3TheDepositTheory132.2.4206070ThePurchasedTheory2.2.5TheMarketingTheory2080[19]1234142.3BalancedManagement2070802.3.11232.3.2152.4[23]Off-Balance-SheetActivity2080[24][25]2.52.5.1161[26]22-1173(a)(b)(c)(d)182.5.212-222-32-2192.5.3[27]1TheSourceandUseofFundsApproach⎟⎟⎠⎞⎜⎜⎝⎛⋅-=Δm,1,,,,dtdpprrmSPIfDpmptspp0)1(,0)(,0,0,0ppfffdtdPpDrrDmDSDPIDpmptspp⋅∂Δ∂-∂Δ∂∂Δ∂∂Δ∂∂Δ∂DΔpPIpSsmpmptrr-dtdPp⋅1m),1,,,,(mtppcpsppddprrmegfL•-=ΔLΔpgGNPpe2-320pcprr-tpddp•1mDΔLΔ)(LDGΔ-Δ=Δ2TheStructureofFundsApproachHotMoneyLiabilityVulnerableFunds/(StableFunds/CoreLiability)3LiquidityIndicatorApproach[28]21[29][27]2233.118%3-13-120005.38%-8.31%6.51%20015.76%-8.3%6.88%20025.54%-8.15%6.91%22002234.264.725.143.9925.52%22.37%15.36%228981568837%3-2200225.52%-22.37%15.36%4.26%4.72%5.14%3.99%33-320000.145%2.80%0.298%6.57%0.014%0.225%0.104%2.20%3.58%7.66%1.474%23.99%[30]3-3200113.45%16.35%20.11%15.38%200012.41%14.85%32.02%15.02%2443-4200170%3-4200085.80%88.23%66.77%83.18%200186.76%87.33%75.64%85.66%519973-5200126785.443-520019210.044452.337596.35526.7726785.4420008349.283245.466238.985353.323187.0219995561.5628.495544.883312.3414447.27253.2Whatifscenario[31]3.3126232744.14-11234-12844.2[32][33]4.2.11[2]4-14-11.1.2.2.3.3.4.4.5.5.6.6.7.29[34]24.2.2[35][36]111x/12x/3013x/111125%14x%100×++++15x/75%3116x/120%17x/18x/---4%8%221x--22x/3223x/24x/25x100×-26x33331x/32x/441x42x143x144x4.34.3.11234[37]3[38]4.3.2123GM4GM1nGM5GM4.3.3GM(1,1))],(,),2(),1([)0()0()0()0(nXXXXL=4-135)0(X4-24-34-4GM(11)n4n-3)0(iX)0(X)0(iX)0(X)0(XGM111)](,),2(),1([)0()0()0()0(nXXXXiL=4-52{}{})1()0(iiXX→4-6)](,),2(),1([)1()1()1()1(nXXXXiL=4-7∑==tkkXtX1)0()1()()(4-83BnY⎥
本文标题:商业银行流动性风险集成式评价模型及实现研究
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