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GARCH Time Series Models: An Application to Retail Livestock Prices

Satheesh Aradhyula () and Matthew Holt ()

Center for Agricultural and Rural Development (CARD) Publications from Center for Agricultural and Rural Development (CARD) at Iowa State University

Abstract: Traditional time series models assume a constant conditional variance. Realizing the implausibility of this assumption, Bollerslev proposed Generalized Autoregressive Conditional Heteroscedasticity (GARSH) processes, which are characterized by nonconstant conditional variances. In this paper, GARCH (1,1) processes were applied to model livestock prices. Results indicate that GARCH processes adequately describe retail meat price behavior.

Date: 1988-05
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Related works:
Journal Article: GARCH TIME-SERIES MODELS: AN APPLICATION TO RETAIL LIVESTOCK PRICES (1988) Downloads
Working Paper: GARCH Time Series Models: An Application to Retail Livestock Prices (1988) Downloads
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