?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.relation=https%3A%2F%2Fpublications.ut-capitole.fr%2Fid%2Feprint%2F45033%2F&rft.title=Inference+for+extremal+regression+with+dependent+heavy-tailed+data&rft.creator=Daouia%2C+Abdelaati&rft.creator=Stupfler%2C+Gilles+Claude&rft.creator=Usseglio-Carleve%2C+Antoine&rft.subject=B-+ECONOMIE+ET+FINANCE&rft.description=Nonparametric+inference+on+tail+conditional+quantiles+and+their+least+squares+analogs%2C+expectiles%2C+remains+limited+to+i.i.d.+data.+Expectiles+are+themselves+quan-+tiles+of+a+transformation+of+the+underlying+distribution.+We+develop+a+fully+operational+kernel-based+inferential+theory+for+extreme+conditional+quantiles+and+expectiles+in+the+challenging+framework+of+%E2%86%B5-mixing%2C+conditional+heavy-tailed+data+whose+tail+index+may+vary+with+covariate+values.++This+extreme+value+problem+requires+a+dedicated+treatment+to+deal+with+data+sparsity+in+the+far+tail+of+the+response%2C+in+addition+to+handling+diffi++culties+inher-+ent+to+mixing%2C++smoothing%2C++and+sparsity+associated+to+covariate+localization.++We+prove+the+pointwise+asymptotic+normality+of+our+estimators+and+obtain+optimal+rates+of+convergence+reminiscent+of+those+found+in+the+i.i.d.+regression+setting%2C+but+which+had+not+been+estab-+lished+in+the+conditional+extreme+value+literature+so+far.+Our+mathematical+assumptions+are+satisfied+in+location-scale+models+with+possible+temporal+misspecification%2C+nonlinear+regression+models%2C+and+autoregressive+models%2C+among+others.+We+propose+full+bias+and+variance+reduction+procedures%2C+and+simple+but+e%E2%86%B5ective+data-based+rules+for+selecting+tun-+ing+hyperparameters.+Our+inference+strategy+is+shown+to+perform+well+in+finite+samples+and+is+showcased+in+applications+to+stock+returns+and+tornado+loss+data.&rft.publisher=TSE+Working+Paper&rft.date=2022-03&rft.type=Monograph&rft.type=NonPeerReviewed&rft.format=text&rft.language=en&rft.identifier=https%3A%2F%2Fpublications.ut-capitole.fr%2Fid%2Feprint%2F45033%2F1%2Fwp_tse_1324.pdf&rft.identifier=++Daouia%2C+Abdelaati+%3Chttps%3A%2F%2Fwww.idref.fr%2F076657000%3E%2C+Stupfler%2C+Gilles+Claude+%3Chttps%3A%2F%2Fwww.idref.fr%2F159301602%3E+and+Usseglio-Carleve%2C+Antoine+%3Chttps%3A%2F%2Fwww.idref.fr%2F23039521X%3E++(2022)+Inference+for+extremal+regression+with+dependent+heavy-tailed+data.++TSE+Working+Paper%2C+n.+22-1324%2C+Toulouse+++++&rft.relation=http%3A%2F%2Ftse-fr.eu%2Fpub%2F126785&rft.language=en