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Results tagged with garch
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user 51228
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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EGARCH and GARCH effects with White Noise squared residuals
I'm asked to model a series which it's returns are white noise and after adjusting a regression like $r_t=c$ and looking it's squared residuals (white noise too) I'm asked to adjust a GARCH and EGARCH … Surprisingly, all coefficients both in GARCH and EGARCH are significative, how is this possible if the squared residuals were white noise? …
