{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T03:00:59Z","timestamp":1791255659848,"version":"4.1.0"},"reference-count":33,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2002,10,28]],"date-time":"2002-10-28T00:00:00Z","timestamp":1035763200000},"content-version":"vor","delay-in-days":57,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2002,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Theoretical and practical interest in non\u2010linear time series models, particularly regime switching models, have increased substantially in recent years. Given the abundant research activity in analysing time\u2010varying volatility through Generalized Autoregressive Conditional Heteroscedasticity (GARCH) processes (see Engle,<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"#bib9\">1982<\/jats:ext-link>; Bollerslev,<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"#bib2\">1986<\/jats:ext-link>), it is important to analyse regime switching models with GARCH errors. A popular specification in this class is the (stationary) Smooth Transition Autoregressive\u2013GARCH (STAR\u2010GARCH) model. Little is presently known about the structure of the model, or the consistency, asymptotic normality and finite sample properties of the estimators. The paper develops the structural and statistical properties of the STAR\u2010GARCH model, and investigates the finite sample properties of maximum likelihood estimation (MLE) of STAR and STAR\u2010GARCH models through numerical simulation. The effects of fixing the threshold value and\/or the transition rate for the STAR model, misspecification of the conditional mean and the transition function of the STAR\u2010GARCH model, and the finite sample properties of the MLE for the STAR\u2010GARCH model, are also examined. These numerical results are used as a guide in empirical research, with an application to Standard and Poor's Composite 500 Index returns for alternative STAR\u2010GARCH models. Copyright \u00a9 2002 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.686","type":"journal-article","created":{"date-parts":[[2002,10,29]],"date-time":"2002-10-29T13:56:52Z","timestamp":1035899812000},"page":"509-534","source":"Crossref","is-referenced-by-count":50,"title":["Maximum likelihood estimation of STAR and STAR\u2010GARCH models: theory and Monte Carlo evidence"],"prefix":"10.1002","volume":"17","author":[{"given":"Felix","family":"Chan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"McAleer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2002,10,28]]},"reference":[{"key":"e_1_2_7_2_1","first-page":"653","article-title":"Estimation and inference in non\u2010linear structural models","volume":"3","author":"Berndt E","year":"1974","journal-title":"Annals of Economic and Social Measurement"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(86)90063-1"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/0304-4076(92)90067-2"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0764-4442(00)01593-7"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-2070(00)00070-4"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1081\/ETC-120008723"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/0927-5398(93)90006-D"},{"key":"e_1_2_7_9_1","first-page":"1255","article-title":"Consistency in heteroskedastic models","volume":"320","author":"Elie L","year":"1995","journal-title":"Comptes Rendus de l'Acad\u00e8mie des Sciences"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.2307\/1912773"},{"key":"e_1_2_7_11_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511754067"},{"key":"e_1_2_7_12_1","unstructured":"FransesP NeeleJ van DijkD.1998.Forecasting volatility with switching persistence GARCH models.Econometric Institute Report EI\u20109819."},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/68.1.189"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-4076(98)00089-X"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466699156032"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466698141038"},{"key":"e_1_2_7_17_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1239\/jap\/1032374627","article-title":"On the probabilitistic properties of a double threshold ARMA conditional heteroscedasticity model","volume":"36","author":"Ling S","year":"1999","journal-title":"Journal of Applied Probability"},{"key":"e_1_2_7_18_1","doi-asserted-by":"crossref","first-page":"1184","DOI":"10.1080\/01621459.1997.10474076","article-title":"On fractional integrated autoregressive moving average time series models with conditional heteroscedasticity","volume":"92","author":"Ling S","year":"1997","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466602183071"},{"key":"e_1_2_7_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-4076(01)00090-2"},{"key":"e_1_2_7_21_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0266466602183071"},{"key":"e_1_2_7_22_1","article-title":"On adaptive estimation in nonstationary models with GARCH errors","author":"Ling S","year":"2002","journal-title":"Annals of Statistics"},{"key":"e_1_2_7_23_1","unstructured":"LundberghS Ter\u00e4svirtaT.1999.Modelling economic high frequency time series with STAR\u2010STGARCH models. 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