Fractionally integrated generalized autoregressive conditional heteroskedasticity, Journal of Econometrics 7 A: 3-30.
What does GARCH stand for?
GARCH stands for Generalized Autoregressive Conditional Heteroskedasticity
This definition appears very frequently
We have 2 other meanings of GARCH in our Acronym Attic
- Grassroots Animal Rights Conference
- Great American Rifle Conference
- Great American Royal Circus (Jacksonville, FL)
- Greater Ardoyne Residents Collective (UK)
- Greenough Advanced Rescue Craft (rescue boat; Rapid Response Technology, LLC)
- Greenwood Amateur Radio Club (Greenwood, Nova Scotia, Canada)
- Grenada Amateur Radio Club
- Griffin Area Resource Center (Georgia)
- Guelph Amateur Radio Club
- Greater Augusta Regional Chamber of Commerce (Virginia)
- Greater Arnold Recreation Council Incorporated
- Guardian Angel Regional Catholic School (Staunton Park, VA)
- Gangable Audio Rack Doors (Raxxess)
- Gemeinnützige Ambulanz und Rettungsdienst Gmbh (medical transport company; Hamburg, Germany)
- General Address Reading Device
- Genetic and Rare Diseases
- Global Alliance Against Chronic Respiratory Diseases
- Gracie Air Rage Defense (Gracie Jiu-Jitsu Academy)
- Georgia Association of Regional Development Centers
- Gilberts Agricultural and Rural Development Center
Samples in periodicals archive:
Then we shifted to Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model for determining long-run impact of exchange rate on the inflation rate.
[FIGURE 1 OMITTED] Mishra and Rahman (2010) examined the dynamics of stock market returns volatility of India and Japan using the Threshold Generalized Autoregressive Conditional Heteroskedasticity (TGARCH-M) model.
They documented a positive conditional volatility--volume relationship in models with Gaussian errors and Generalized Autoregressive Conditional Heteroskedasticity (GARCH)-type volatility specifications.
1) The discrete-time approximation of the continuous-time specification is then formulated as a generalized autoregressive conditional heteroskedasticity (GARCH) framework introduced by Bollerslev (1986).
Introduction Generalized autoregressive conditional heteroskedasticity models (GARCH) are quite popular all over the world.
Second, to measure the effects of both expected and unexpected inflation and inflation uncertainty, we employ generalized autoregressive conditional heteroskedasticity (GARCH)-type models to obtain expected and unexpected components of inflation and conditional variance as a proxy for inflation uncertainty.
Fortunately, prior research indicates that Generalized Autoregressive Conditional Heteroskedasticity (Engel, 1982) model of the first order, i.