{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T09:41:43Z","timestamp":1789724503355,"version":"4.0.1"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2002,5,15]],"date-time":"2002-05-15T00:00:00Z","timestamp":1021420800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2002,6]]},"abstract":"<jats:p>Because the empirical characteristic function (ECF) is the \nFourier transform of the empirical distribution function, it \nretains all the information in the sample but can overcome \ndifficulties arising from the likelihood. This paper discusses \nan estimation method via the ECF for strictly stationary processes. \nUnder some regularity conditions, the resulting estimators are \nshown to be consistent and asymptotically normal. The method \nis applied to estimate the stable autoregressive moving average \n(ARMA) models. For the general stable ARMA model for which the \nmaximum likelihood approach is not feasible, Monte Carlo evidence \nshows that the ECF method is a viable estimation method for \nall the parameters of interest. For the Gaussian ARMA model, \na particular stable ARMA model, the optimal weight functions \nand estimating equations are given. Monte Carlo studies highlight \nthe finite sample performances of the ECF method relative to \nthe exact and conditional maximum likelihood methods.<\/jats:p>","DOI":"10.1017\/s026646660218306x","type":"journal-article","created":{"date-parts":[[2003,10,16]],"date-time":"2003-10-16T10:06:57Z","timestamp":1066298817000},"page":"691-721","source":"Crossref","is-referenced-by-count":70,"title":["EMPIRICAL CHARACTERISTIC FUNCTION IN TIME SERIES ESTIMATION"],"prefix":"10.1017","volume":"18","author":[{"given":"John L.","family":"Knight","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2002,5,15]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S026646660218306X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T19:50:55Z","timestamp":1554407455000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S026646660218306X\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2002,5,15]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2002,6]]}},"alternative-id":["S026646660218306X"],"URL":"https:\/\/doi.org\/10.1017\/s026646660218306x","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2002,5,15]]}}}