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ID:28822205
大小:7.39 MB
页数:52页
时间:2018-12-14
《基于区制转移模型的短期利率动态行为分析》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、基于区制转移模型的短期利率动态行为研究AbstTaCtThedynamiebehaviorofshort一terminterestratesPlaysaveryimPortantroleonfixed一ineomeseeuritiesandinterestratederivatives.Sineeunderstandofthedynamiesoftheshort一terminterestrateseanhelPtodiseoverthePrieesoffinaneialProduets,managetheriskofinterestrates.Short一terminteres
2、trate15animPortantbusinesseyelevariable,whieh15imPortantfortheformulationofmonetaryPolieyandthesensitivityofinflationexPectations.Thxoughanalysisofthedynamicbehaviorofshort一terminterestrates,maeroeeonomicPolieieseanbeeffeetivetoadapttoeconomieeyelesandchangesininflationexPectations,evaluatio
3、noftheeffeetsofeeonomiePoliey.Therefore,alargenumberofdomesticandforeignseholarseonduetresearehonshort一terrniflterestrates.BlltmostofthestudiesbasedonBrownianmotiontodeseribethedynamiebehaviorofshort一terminterestrate,50thesamPlePatllofshort一terminterestrate15alwayseontinuous,Howeveralargenum
4、berofemPiriealstudiesfoundthatthesamPlerate15notalwayseoutinuous,therewillbestructuralehangesininterestratebehavior.Infact,short一termratesinChinaaetuallyundergosignifieantstrueturalehangesandinterestratevolatilityhasobviousboundaries.Therefore,it15neeessarytotakeintoaeeountthestrueturalehang
5、esinshort一terminterestratestoeaPturethetime一varyingstateoftheeconomieehanges.ThisstudyfoeusonthreeasPeets.Firstly,toextendthesinglefactorinterestmodel一CKLSbasedontheregimeswitehingmodel.Theregimevariablefollowsacontinuoustimetwo一stateMarkovehain.Seeondly,intruduetingthedetailsofatheoryestabl
6、ishedbyAi’t一Sahalia(2002)toapProximatethetruedensityfunetionofanarbitraryunivariatedi饰sionProeessinelosedform.ThenhighlyaeeuratetransitiondensityfunetionofthediffusionProeess15usedwheneonstruetingthelikelihoodfunetionbyaPPlyingthereeursivealgorithmdeveloPedbyHamilton(1989).Therefore,ourstudy
7、doesnotsufferfromdiseretizationbias.Finally,eonductingouremPiriealanalysisofshort一terminterestratesthroughmaximumlikelihoodestimationandeomParingourmodelwithmodelsofVasieekandCIR.ThemaximumlikelihoodestimatesareobtainedusingthedailyseriesofChinasev
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