Autoregressive conditional heteroskedasticity
In econometrics,
an autoregressive conditional heteroskedasticity (ARCH) model considers the variance of the current error term to be a function of the variances of the previous time periods' error terms.
If an autoregressive moving average model is assumed for the error variance, the model is a generalized autoregressive conditional heteroskedasticity (GARCH) model.
Generally, when testing for heteroskedasticity in econometric models, the best test is the White test. However, when dealing with time series data, the best test is Engle's ARCH test.
References
- Tim Bollerslev. "Generalized Autorregressive Conditional Heteroskedasticity", Journal of Econometrics, 31:307-327, 1986.
