Forecasting Hog Prices with a Neural Network

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dc.creatorHamm, Lonnie
dc.creatorBrorsen, B. Wade
dc.date2017-04-01T18:52:02Z
dc.date.accessioned2026-07-09T05:14:02Z
dc.descriptionNeural network models were compared to traditional forecasting methods in forecasting the quarterly and monthly farm price of hogs. A quarterly neural network model forecasted poorly in comparison to a quarterly econometric model. A monthly neural network model outperformed a monthly ARIMA model with respect to the mean square error criterion and performed similarly to the ARIMA model with respect to turning point accuracy. The more positive results of the monthly neural network model in comparison to the quarterly neural network model may be due to nonlinearities in the monthly data which are not in the quarterly data.
dc.identifierOther:0738-8950
dc.identifierdoi:10.22004/ag.econ.90646
dc.identifierhttps://ageconsearch.umn.edu/record/90646/files/JAB15one3.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/90646
dc.identifier.urihttp://hdl.handle.net/123456789/560862
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/90646
dc.titleForecasting Hog Prices with a Neural Network
dc.typeText

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