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The specific purpose of this paper is to investigate the potential of a time series analysis technique, namely the Time Varying Parameter Vector Autoregressive Model (TVPVAR) technique, in the development of daily forecasting models for cattle prices in the presence of structural changes. More specific objectives are to integrate smoothing techniques and stochastic volatility into TVPAR modeling framework based exclusively on time series for cash-cattle prices, and to compare the accuracy and evaluate the forecasting performance of this model with the standard VAR model based on forecast accuracy measures.


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