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autoregressive conditional heteroscedasticity model


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A time series model in which the random error is conditionally heteroscedastic with respect to its past realizations. This model is used to describe volatility clustering, i.e. a pattern observed in many financial data where large and small forecast errors appear to occur in clusters. The simplest form is ARCH (1),

yt = βxt + εt

where and ut has a standard normal distribution.

Subjects: Economics.


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