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ARIMA(自己回帰和分移動平均)モデル×指数 GARCH (EGARCH)×長期記憶モデル(ARFIMA、FIGARCH)×
分野計量経済学計量経済学ファイナンス
系統Regression modelRegression modelRegression model
提唱年201519911980
提唱者Box & Jenkins (Box-Jenkins methodology)NelsonGranger & Joyeux (ARFIMA); Baillie, Bollerslev & Mikkelsen (FIGARCH)
種類Univariate time-series modelConditional volatility model (asymmetric GARCH variant)Fractionally integrated time series model
原典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 ↗Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15-29. DOI ↗
別名Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeliexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHARFIMA, FIGARCH, fractionally integrated models, fractional integration
関連544
概要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.Long-memory models are fractional-integration methods that capture genuine long memory through a hyperbolically decaying autocorrelation structure. ARFIMA, introduced by Granger and Joyeux (1980), models long memory in return series, while FIGARCH, introduced by Baillie, Bollerslev and Mikkelsen (1996), captures long memory in volatility series; the parameter d measures the degree of fractional integration.
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ScholarGate手法を比較: ARIMA · EGARCH · Long-Memory Models. 2026-06-19に以下より取得 https://scholargate.app/ja/compare