What does ARCH stand for?

Autoregressive Conditional Heteroskedasticity

This definition appears very rarely and is found in the following Acronym Finder categories:

Science, medicine, engineering, etc.

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Samples in periodicals archive:

We propose three alternative specifications of expected future beta based on the past information on realized beta using autoregressive, moving average, and generalized autoregressive conditional heteroskedasticity (GARCH)-in-mean models to obtain time-varying conditional betas for each stock.

The conditional beta and the cross-section of expected returns

Finally, we jointly model the impact of the expiration of these contracts on the returns to the market index and the volatility of these returns, using generalised autoregressive conditional heteroskedasticity (GARCH) models.

Impact of derivatives trading on emerging stock markets: some ...

Secondly, as a check on these results, we will employ a generalized autoregressive conditional heteroskedasticity (GARCH) (1) model.

Changing inflation dynamics and uncertainty in the United States

Engle received the prize for his research on the concept of autoregressive conditional heteroskedasticity (ARCH).

NYU Stern's Engle Wins 2003 Nobel Prize in Economics

In his Nobel Laureate lecture Engle assumed the returns on the S&P 500 had a normal distribution and then estimated volatility using his well-known autoregressive conditional heteroskedasticity model.

Asymmetric volatility, risk and filtered historical simulation

In this study, we examine the short-run dynamic information transmission between the Chinese A and B share markets using a Bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) framework, which simultaneously models the return transmission and volatility spillover across the two markets.

Short-term dynamic transmission and long-term foreign share discount: ...

The most popular one is the class of autoregressive conditional heteroskedasticity (ARCH) models, introduced by Engle (1982).

Risk management: an analysis of the low-tail behavior of high ...

This is done by estimating a two-variable vector autoregression (VAR) model in which it is assumed that the disturbances follow a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) process.

The correlation between shocks to output and the price level: ...