Publicação
Predicting demand using autoregressive integrated moving average (Arima) - application on the Iberian market for clams
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Gardete, Pedro | |
| dc.contributor.author | Moissiadis, Nicolas Charalampos | |
| dc.date.accessioned | 2024-02-02T14:29:29Z | |
| dc.date.available | 2024-02-02T14:29:29Z | |
| dc.date.issued | 2023-01-19 | |
| dc.date.submitted | 2022-12-13 | |
| dc.description.abstract | 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. | pt_PT |
| dc.identifier.tid | 203314565 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/163025 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Clams | pt_PT |
| dc.subject | Demand forecasting | pt_PT |
| dc.subject | Arima | pt_PT |
| dc.subject | Hyperparameter tuning | pt_PT |
| dc.subject | Statistical forecasting | pt_PT |
| dc.subject | Python | pt_PT |
| dc.title | Predicting demand using autoregressive integrated moving average (Arima) - application on the Iberian market for clams | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master9s degree in Business Analytics from the Nova School of Business and Economics. | pt_PT |