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ARIMA (Autoregressive Integrated Moving Average) -malli×Johansenin kointegraatiotesti ja vektorikorjausmalli×
TieteenalaEkonometriaRahoitus
MenetelmäperheRegression modelRegression model
Syntyvuosi20151991
KehittäjäBox & Jenkins (Box-Jenkins methodology)Søren Johansen
TyyppiUnivariate time-series modelMultivariate cointegration / vector error correction model
AlkuperäislähdeBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580. DOI ↗
RinnakkaisnimetBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliJohansen test, VECM, vector error correction model, multivariate cointegration
Liittyvät53
TiivistelmäARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.
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ScholarGateVertaile menetelmiä: ARIMA · Johansen Cointegration Test. Haettu 2026-06-19 osoitteesta https://scholargate.app/fi/compare