- Determine the features governing coffee price.
- Assess the importance of each feature.
- Forcast the price of commodity coffee.
As weather is a major contributer production affecting both yield and disease, weather would be a major predictor of price.
Weather alone is not able to forcast the price and so it would need to be combined with production and export/import data.
As the weather and production data are highly seasonal, Seasonal data decomposed from past data plus scalling from weather and production forcast could be used as features in forcasting the future price.
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According to the Global Exchange, there are approximately 25 million farmers in over 50 countries involved in producing coffee
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Seventy percent of coffee beans are Arabica. Although less popular, Robusta is slightly more bitter and has twice as much caffeine.
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Coffee is a popular commodity -> huge global demand
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Coffee commodity is one of the volatile commodities -> weather is major contributing factor.
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Arabica coffee is the world benchmark for coffee futures contracts that trade on the Intercontinental Exchange (ICE).
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Arabica mostly cultivated in Brazil: 40% of world’s total supply
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Major exporters are : Columbia, Peru, India, Uganda, Ethiopia, Mexico, Cote Ivoire.
Weather data alone did not provide addiquate forcasting ability so hypothesis 2 was used to forcast the data.
Training Adj. R^2 = 0.905
Testing Adj. R^2 = -8.7
MSE = 1353.5
MAE = $31.02
Training Adj. R^2 = 0.683
Testing Adj. R^2 = 0.371
MSE = 87.78
MAE = $7.165
MAE = $12.84
The final model was made as a combination of the Lasso regression
Mean Absolute Error = $7.165
