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Results tagged with garch
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user 39005
Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used for time series in which the conditional variance is time-varying and autocorrelated. The conditional variance is a linear combination of lagged conditional variances and lagged squared errors. The conditional variance equation in GARCH models is deterministic, in contrast to Stochastic Volatility (SV) models.
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Standard GARCH(1,1) model with external regressors
I have a queastion how does a standard GARCH(1,1) model with external regressors in mean and variance euqations look like ? … I know that standard GARCH(1,1) model without external regressors has the following form:
\begin{equation*}
r_t = \mu + \epsilon_t
\end{equation*}
\begin{equation*}
\epsilon_t = \sigma_t z_t
\end{equation …
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