Comparar métodos

	Volatilidade Realizada e o Modelo HAR	Exponential GARCH (EGARCH)	Teste de Cointegração de Johansen e Modelo de Vetor de Correção de Erros
Área	Finanças	Econometria	Finanças
Família	Regression model	Regression model	Regression model
Ano de origem	2009	1991	1991
Autor original	Corsi (HAR model); Andersen, Bollerslev, Diebold & Labys (realized volatility)	Nelson	Søren Johansen
Tipo	Time-series regression of realized variance	Conditional volatility model (asymmetric GARCH variant)	Multivariate cointegration / vector error correction model
Fonte seminal	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196.	Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370.	Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580.
Outros nomes	realized variance, HAR model, heterogeneous autoregressive model of realized volatility, HAR-RV	exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH	Johansen test, VECM, vector error correction model, multivariate cointegration
Relacionados	5	4	3
Resumo	Realized volatility estimates an asset's variance directly from high-frequency intraday returns rather than from a parametric latent process. The Heterogeneous Autoregressive (HAR) model of Corsi (2009), building on the realized-volatility framework of Andersen, Bollerslev, Diebold and Labys (2003), forecasts this measure by combining daily, weekly, and monthly volatility components, and is a strong alternative to GARCH for volatility prediction.	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.	The Johansen procedure is a multivariate cointegration framework, introduced by Søren Johansen in 1991, that tests for long-run equilibrium relationships among several I(1) time series. It determines how many cointegrating vectors link the series and then builds a Vector Error Correction Model (VECM) to describe the short-run dynamics around that equilibrium.