Grivas, Charisios (2021): An Automatic Portmanteau Test For Nonlinear Dependence.
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Abstract
A data-driven version of a portmanteau test for detecting nonlinear types of statistical dependence is considered. An attractive feature of the proposed test is that it properly controls type I error without depending on the number of lags. In addition, the automatic test is found to have higher power in simulations when compared to the McLeod and Li test, for both raw data and residuals.
Item Type: | MPRA Paper |
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Original Title: | An Automatic Portmanteau Test For Nonlinear Dependence |
Language: | English |
Keywords: | ARMA time series;Akaike's AIC;Schwarz's BIC; Portmanteau test; Data-driven test |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics |
Item ID: | 114312 |
Depositing User: | Mr Charisios Grivas |
Date Deposited: | 06 Sep 2022 20:19 |
Last Modified: | 06 Sep 2022 20:19 |
References: | G.E.P.Box,D.A.Pierce,Distributionofresidualautocorrelationsinautoregressive-integratedmovingaveragetimeseriesmodels,Journal of the American Statistical Association 65 (332) (1970) 1509–1526. G.M.Ljung,G.E.P.Box,Onameasureoflackoffitintimeseriesmodels,Biometrika65(2)(1978)297–303. URL http://www.jstor.org/stable/2335207 G.E.P.Box,G.Jenkins,TimeSeriesAnalysis,ForecastingandControl,Holden-Day,Inc.,USA,1990. P.J.Brockwell,R.A.Davis,Timeseries:theoryandmethods,Springerscience&businessmedia,2009. A.A.P.GrangerC.W.J.,Anintroductiontobilineartimeseriesmodels.,Vandenhoeck&Ruprecht,Gottingen,1978. A. I. McLeod, W. K. Li, Diagnostic checking arma time series models using squared-residual autocorrelations, Journal of Time Series Analysis 4 (4) (1983) 269–273 R.Luukkonen,P.Saikkonen,T.Teräsvirta,Testinglinearityinunivariatetimeseriesmodels,ScandinavianJournalofStatistics15(3)(1988) 161–175. Z. Psaradakis, M. Vávra, Portmanteau tests for linearity of stationary time series, Econometric Reviews 38 (2) (2019) 248–262. J.C.Escanciano,I.N.Lobato,Anautomaticportmanteautestforserialcorrelation,JournalofEconometrics151(2)(2009)140–149,recent Advances in Time Series Analysis: A Volume Honouring Peter M. Robinson. T.Inglot,T.Ledwina,Towardsdatadrivenselectionofapenaltyfunctionfordatadrivenneymantests,LinearAlgebraanditsApplications 417 (2006) 124–133. G.Schwarz,Estimatingthedimensionofamodel,Ann.Statist.6(2)(1978)461–464. H.Akaike,Anewlookatthestatisticalmodelidentification,IEEETransactionsonAutomaticControl19(6)(1974)716–723. J.Kreiss,Estimationofthedistributionfunctionofnoiseinstationaryprocesses,Metrika:InternationalJournalforTheoreticalandApplied Statistics 38 (1) (1991) 285–297. G. M. Kuersteiner, Optimal instrumental variables estimation for arma models, Journal of Econometrics 104 (2) (2001) 359 – 405. T. W. Anderson, The asymptotic distributions of autoregressive coefficients, Tech. rep., STANFORD UNIV CA DEPT OF STATISTICS (1991). A. Pérez, E. Ruiz, Properties of the Sample Autocorrelations of Nonlinear Transformations in Long-Memory Stochastic Volatility Mod- els, Journal of Financial Econometrics 1 (3) (2003) 420–444. H.Leeb,B.M.Pötscher,Modelselectionandinference:Factsandfiction,EconometricTheory(2005)21—-59. L.Fenga,D.N.Politis,Bootstrap-basedarmaorderselection,JournalofStatisticalComputationandSimulation81(2011)799–814. P. M. T. Broersen, S. de Waele, Finite sample properties of arma order selection, IEEE Transactions on Instrumentation and Measurement 53 (3) (2004) 645–651. S.T.Buckland,K.P.Burnham,N.H.Augustin,Modelselection:Anintegralpartofinference,Biometrics53(2)(1997)603–618. A.J.Lawrance,P.A.W.Lewis,Higher-orderresidualanalysisfornonlineartimeserieswithautoregressivecorrelationstructures,International Statistical Review / Revue Internationale de Statistique 55 (1) (1987) 21–35. A.Berg,E.Paparoditis,D.N.Politis,Abootstraptestfortimeserieslinearity,JournalofStatisticalPlanningandInference140(12)(2010) 3841–3857. S.Giannerini,E.Maasoumi,E.B.Dagum,Entropytestingfornonlinearserialdependenceintimeseries,Biometrika102(3)(2015)661–675. E.J.Hannan,Theasymptotictheoryoflineartime-seriesmodels,JournalofAppliedProbability10(1)(1973)130–145. T.-H.Lee,H.White,C.W.Granger,Testingforneglectednonlinearityintimeseriesmodels:Acomparisonofneuralnetworkmethodsand alternative tests, Journal of Econometrics 56 (3) (1993) 269–290. J. P. Romano, L. A. Thombs, Inference for autocorrelations under weak assumptions, Journal of the American Statistical Association 91 (434) (1996) 590–600. J. C. Escanciano, I. N. Lobato, L. Zhu, Automatic specification testing for vector autoregressions and multivariate nonlinear time series models, Journal of Business & Economic Statistics 31 (4) (2013) 426–437. P.Billingsley,ProbabilityandMeasure,3rdEdition,JohnWileyandSons,1986. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/114312 |