简介:Motivatedbythedoubleautoregressivemodelwithorderp(DAR(p)model),inthispaper,westudythemovingaveragemodelwithanalternativeGARCHerror.ThemodelisanextensionfromDAR(p)modelbylettingtheorderpgoestoinfinity.Thequasimaximumlikelihoodestimatoroftheparametersinthemodelisshowntobeasymptoticallynormal,withoutanystrongmomentconditions.Simulationresultsconfirmthatourestimatorsperformwell.WealsoapplyourmodeltostudyarealdatasetandithasbetterfittingperformancecomparedtoDARmodelfortheconsidereddata.
简介:Thegeneralizedautoregressiveconditionalheteroskedasticity(GARCH)typemodelsareusedtoinvestigatethevolatilityofBangladeshstockmarket.Thefindingsofthestudydemonstratethattheindexvolatilitycharacteristicschangesovertime.Thearticleshowsthatthedataaredividedintothreesub-periods:precrisis,crisis,andpostcrisis.Accordingly,theresultsofthefindingsindicatechangesintheGARCH-typemodelsparameter,riskpremiumandpersistenceofvolatilityindifferentperiods.Asignificant'low-yieldassociatedwithhigh-risk'phenomenonisdetectedinthecrisisperiodandthe'leverageeffect'occursineachperiods.Theinvestorsareirrationalwhichisbasedonassumptionofriskandreturncharacteristicsofassets.Consequently,themarketisnotasmatureasdevelopedmarket.Itisfoundinthearticlethatthethresholdgeneralizedautoregressiveconditionalheteroskedasticity(TGARCH)modelismoreaccurateforthemodelaccuracy.Additionally,statisticerrormeasurementsindicatethatGARCHmodelismoreefficientthanothersandithasalsomoreforecastingability.