Comparar métodos

	Modelo TGARCH com Parâmetros Variáveis no Tempo	Modelo GARCH (Previsão de Volatilidade)
Área	Econometria	Econometria
Família	Regression model	Regression model
Ano de origem	1990s–2000s	1986
Autor original	Extension combining Zakoïan (1994) TGARCH and time-varying parameter methods	Tim Bollerslev
Tipo	Volatility model with asymmetry and parameter evolution	Conditional volatility model
Fonte seminal	Zakoïan, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Outros nomes	TVP-TGARCH, time-varying TGARCH, threshold GARCH with time-varying parameters, TVP Threshold GARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relacionados	4	5
Resumo	The TVP-TGARCH model extends Threshold GARCH by allowing its volatility parameters to evolve over time via a state-space representation. It captures both the leverage effect — that negative return shocks increase volatility more than positive ones — and structural change in that asymmetry, making it well-suited for long financial time series subject to regime shifts.	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.