Regression model
GARCH Model (Volatility Forecasting)
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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Sources
- Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI: 10.1016/0304-4076(86)90063-1 ↗
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Referenced by
APARCHARCH modelBayesian ARCH modelBayesian GARCH modelBEKK-GARCHEGARCH modelFourier ARCH ModelFourier DCC-GARCHGJR-GARCHHAR-RV ModelJump-Diffusion ModelLong-Memory ModelsMarkov-Switching MultifractalNonlinear ARCH modelNonlinear ARIMA modelNonlinear EGARCH modelNonlinear MA modelNonlinear SARIMA ModelNonlinear TGARCH modelRobust ARCH modelRobust DCC-GARCHRobust EGARCHRobust GARCH modelStochastic Volatility ModelStructural Break ARCH ModelStructural Break TGARCHTail Risk MeasuresTGARCH modelTime-varying parameter ARCH modelTime-varying parameter DCC-GARCH modelTime-varying parameter EGARCH modelTime-varying parameter GARCH modelTime-varying parameter TGARCH modelVaR Backtesting