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非対称パワーARCH (APARCH): 金融リターンの柔軟なボラティリティ・モデリング×GARCHモデル(ボラティリティ予測)×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年19931986
提唱者Ding, Granger & EngleTim Bollerslev
種類Conditional heteroscedasticity modelConditional volatility model
原典Ding, Z., Granger, C. W. J., & Engle, R. F. (1993). A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1(1), 83–106. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
別名Asymmetric Power ARCH, Power ARCH, APGARCH, Asimetrik Güç ARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
関連35
概要APARCH, introduced by Ding, Granger, and Engle (1993) while studying long-memory properties of stock market returns, extends the GARCH family by allowing both the power transformation of conditional volatility and an asymmetric response to positive and negative shocks. The model nests at least seven well-known ARCH-type specifications as special cases, making it a unifying framework for volatility modelling in financial econometrics.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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ScholarGate手法を比較: APARCH · GARCH Model. 2026-06-17に以下より取得 https://scholargate.app/ja/compare