autoregressive conditional heteroskedasticity
- autoregressive conditional heteroskedasticity
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A nonlinear stochastic process, where the variance is time-varying, and a function of the past variance. ARCH processes have frequency distributions which have high peaks at the mean and fat-tails, much like fractal distributions. The ARCH model was invented by Robert Engle. The Generalized ARCH (GARCH) model is the most widely used and was pioneered by Tim Bollerslev. Bloomberg Financial Dictionary
See: fractal distributions. Bloomberg Financial Dictionary
Financial and business terms.
2012.
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Autoregressive conditional heteroskedasticity — ARCH redirects here. For the children s rights organization, see Action on Rights for Children. In econometrics, AutoRegressive Conditional Heteroskedasticity (ARCH) models are used to characterize and model observed time series. They are used… … Wikipedia
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Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Process — An econometric term developed in 1982 by Robert F. Engle, an economist and 2003 winner of the Nobel Memorial Prize for Economics to describe an approach to estimate volatility in financial markets. There are several forms of GARCH modeling. The… … Investment dictionary
Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) — A statistical model used by financial institutions to estimate the volatility of stock returns. This information is used by banks to help determine what stocks will potentially provide higher returns, as well as to forecast the returns of current … Investment dictionary
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