Autoregressive conditional heteroscedasticity (ARCH) model

Updated: Aug 20, 2021

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 dato where large and small deviations appear to occur in clusters.

Autoregressive conditional heteroscedasticity (ARCH) model

Reference: Oxford Press Dictonary of Economics, 5th edt.

Sources & references
Risk disclaimer

Invezz is a place where people can find reliable, unbiased information about finance, trading, and investing – but we do not offer financial advice and users should always carry out their own research. The assets covered on this website, including stocks, cryptocurrencies, and commodities can be highly volatile and new investors often lose money. Success in the financial markets is not guaranteed, and users should never invest more than they can afford to lose. You should consider your own personal circumstances and take the time to explore all your options before making any investment. Read our risk disclaimer >

James Knight
Editor of Education
James is a lead content editor for Invezz. He's an avid trader and golfer, who spends an inordinate amount of time watching Leicester City and the… read more.