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Модель Марковских переключений режимов (MS-AR / MS-VAR)×Модель ARIMA (авторегрессионная интегрированная скользящая средняя)×Экспоненциальный GARCH (EGARCH)×
ОбластьЭконометрикаЭконометрикаЭконометрика
СемействоRegression modelRegression modelRegression model
Год появления198920151991
Автор методаHamilton (1989); Kim & Nelson (1999)Box & Jenkins (Box-Jenkins methodology)Nelson
ТипRegime-switching time series modelUnivariate time-series modelConditional volatility model (asymmetric GARCH variant)
Основополагающий источникHamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
Другие названияregime-switching model, Markov-switching autoregression, MS-AR, MS-VARBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeliexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Связанные554
СводкаThe Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.ARIMA 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).EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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ScholarGateСравнение методов: Markov-Switching Model · ARIMA · EGARCH. Получено 2026-06-19 из https://scholargate.app/ru/compare