Forecasting and selling futures using ARIMA models and a neural network
This study involves comparing the forecasting and trading performance of an ARIMA model and a neural network model. The optimal ARIMA model is selected by choosing the combination of sample size and forecast ahead period that produce the minimum forecast error. Weekly data for two contracts traded o...
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| Language: | en_US |
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2007
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| Online Access: | http://hdl.handle.net/1993/921 |