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| GARCHモデル（ボラティリティ予測）× | 実現ボラティリティのHAR-RVモデル× | |
|---|---|---|
| 分野≠ | 計量経済学 | ファイナンス |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1986 | 2009 |
| 提唱者≠ | Tim Bollerslev | Fulvio Corsi |
| 種類≠ | Conditional volatility model | Linear time-series regression for volatility |
| 原典≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ | Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196. DOI ↗ |
| 別名 | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) | HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility) |
| 関連 | 5 | 5 |
| 概要≠ | 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. | The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility. |
| ScholarGateデータセット ↗ |
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