Short†term salmon price forecasting
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 cus...
Published in: | Journal of Forecasting |
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Online Access: | https://doi.org/10.1002/for.2482 |
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ftrepec:oai:RePEc:wly:jforec:v:37:y:2018:i:2:p:151-169 2023-05-15T15:31:57+02:00 Short†term salmon price forecasting Daumantas Bloznelis https://doi.org/10.1002/for.2482 unknown https://doi.org/10.1002/for.2482 article ftrepec https://doi.org/10.1002/for.2482 2020-12-04T13:31:59Z 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%. Article in Journal/Newspaper Atlantic salmon RePEc (Research Papers in Economics) Journal of Forecasting 37 2 151 169 |
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Open Polar |
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RePEc (Research Papers in Economics) |
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ftrepec |
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unknown |
description |
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%. |
format |
Article in Journal/Newspaper |
author |
Daumantas Bloznelis |
spellingShingle |
Daumantas Bloznelis Short†term salmon price forecasting |
author_facet |
Daumantas Bloznelis |
author_sort |
Daumantas Bloznelis |
title |
Short†term salmon price forecasting |
title_short |
Short†term salmon price forecasting |
title_full |
Short†term salmon price forecasting |
title_fullStr |
Short†term salmon price forecasting |
title_full_unstemmed |
Short†term salmon price forecasting |
title_sort |
short†term salmon price forecasting |
url |
https://doi.org/10.1002/for.2482 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
https://doi.org/10.1002/for.2482 |
op_doi |
https://doi.org/10.1002/for.2482 |
container_title |
Journal of Forecasting |
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37 |
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2 |
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151 |
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169 |
_version_ |
1766362451992903680 |