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基于VaR—GARCH模型的我国商业银行汇率风险分析.docx

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基于VaR—GARCH模型的我国商业银行汇率风险分析 Title:AnalysisofExchangeRateRiskinChina'sCommercialBanksbasedonVaR-GARCHModel Abstract: Foreignexchangeriskhassignificantimplicationsforcommercialbanksoperatinginaneconomytightlyintegratedwiththeglobalfinancialsystem.ThisresearchpaperaimstoanalyzetheexchangerateriskfacedbycommercialbanksinChinausingtheValueatRisk(VaR)-GeneralizedAutoregressiveConditionalHeteroskedasticity(GARCH)model.TheVaR-GARCHapproachallowsforcapturingthevolatilitiesandconditionalcorrelationsinexchangerates,whichareessentialforeffectiveriskmanagementstrategies.ThefindingsofthisstudywillhelpcommercialbanksinChinatoidentify,assess,andmitigateexchangerateriskseffectively. Introduction: TheliberalizationandinternationalizationoffinancialmarketshaveexposedcommercialbanksinChinatoincreasingexchangeraterisks.Exchangeratefluctuationscanimpacttheprofitability,solvency,andoverallfinancialstabilityofcommercialbanks.Therefore,itiscrucialtodeveloprobustriskmanagementframeworksthatconsiderthecharacteristicsanddynamicsofexchangeratemovements.ThispaperfocusesontheVaR-GARCHmodelasacomprehensivetooltoanalyzeandquantifyexchangeraterisksfacedbyChinesecommercialbanks. LiteratureReview: Theliteratureonexchangerateriskmanagementisvastandcoversnumerousmodelsandtechniques.Previousstudieshaveexploreddifferentriskmanagementapproaches,includingVaR,GARCH,andtheircombinations.Someresearchershaveappliedthesemodelstoanalyzeexchangeraterisksindifferentcountries,whileothershavefocusedonspecificsectors.However,limitedresearchhasinvestigatedtheapplicationoftheVaR-GARCHmodeltoanalyzeexchangeraterisksincommercialbanksinChina. Methodology: TheVaR-GARCHmodeliswidelyusedtoanalyzefinancialmarketrisks,includingexchangeraterisks.Itenablestheestimationofthepotentiallossesabankmightfaceatdifferentconfidencelevelswithinaspecifiedtimehorizon.Thismodelincorporatestheautoregressiveconditionalheteroskedasticity(ARCH)methodologytocapturethetime-varyingvolatilityofexchangeratesandtheconditionalcorrelationbetweenexchangera