Short‐term salmon price forecasting |
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Authors: | Daumantas Bloznelis |
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Affiliation: | 1. Research Centre for Operations Research and Business Statistics, KU Leuven, Leuven, Belgium;2. School of Economics and Business, Norwegian University of Life Sciences, Aas, Norway |
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Abstract: | This study establishes a benchmark for short‐term salmon price forecasting. The weekly spot price of Norwegian farmed Atlantic salmon is predicted 1–5 weeks ahead using data from 2007 to 2014. Sixteen alternative forecasting methods are considered, ranging from classical time series models to customized machine learning techniques to salmon futures prices. The best predictions are delivered by k‐nearest neighbors method for 1 week ahead; vector error correction model estimated using elastic net regularization for 2 and 3 weeks ahead; and futures prices for 4 and 5 weeks ahead. While the nominal gains in forecast accuracy over a naïve benchmark are small, the economic value of the forecasts is considerable. Using a simple trading strategy for timing the sales based on price forecasts could increase the net profit of a salmon farmer by around 7%. |
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Keywords: | elastic net regularization financial time series forecasting k‐nearest neighbors salmon price vector error correction model |
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