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Predicting demand using autoregressive integrated moving average (Arima) - application on the Iberian market for clams
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Orientador(es)
Resumo(s)
As the accessibility of data has grown, data-driven pricing and
demand forecasting have become more widespread. However,
early-stage companies are often faced with a great deal of
unpredictability due to a lack of existing data before entering the
market. Therefore, a publicly available database has been consulted
to assess the need for clams and related elements to support the
entrance of Oceano Fresco, a sustainable seafood start-up, into the
Iberian Peninsula market. As a result, ARIMA has been adopted to
anticipate a sales index for every month. This index can then be
utilized to estimate the number of clams Oceano Fresco is capable
of selling the following month based on actual demand factors, a
historical equation model, and the previous year9s sales.
Descrição
Palavras-chave
Clams Demand forecasting Arima Hyperparameter tuning Statistical forecasting Python