Autoregressive Conditional Heteroskedasticity - ARCH


DEFINITION of 'Autoregressive Conditional Heteroskedasticity - ARCH'

An econometric term used for observed time series. ARCH models are used to model financial time series with time-varying volatility, such as stock prices. The ARCH concept was developed by economist Robert F. Engle, for which he won the 2003 Nobel Memorial Prize in Economic Sciences.

BREAKING DOWN 'Autoregressive Conditional Heteroskedasticity - ARCH'

ARCH models assume that the variance of the current error term is related to the size of the previous periods' error terms, giving rise to volatility clustering. This phenomenon is widely observable in financial markets, where periods of low volatility are followed by periods of high volatility and vice versa. For example, volatility for the S&P 500 was unusually low for an extended period during the bull market from 2003 to 2007, before spiking to record levels during the market correction of 2008. ARCH models have become mainstays of arbitrage pricing and portfolio theory.

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  4. Time Series

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  5. Heteroskedasticity

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