Stochastic Predictive Analytics for Stocks in the Newsvendor Problem
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | |
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| _version_ | 1866909905502339072 |
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| author | Pury, Pedro A. |
| author_facet | Pury, Pedro A. |
| contents | This work addresses a key challenge in inventory management by developing a stochastic model that describes the dynamic distribution of inventory stock over time without assuming a specific demand distribution. Our model provides a flexible and applicable solution for situations with limited historical data and short-term predictions, making it well-suited for the Newsvendor problem. We evaluate our model's performance using real-world data from a large electronic marketplace, demonstrating its effectiveness in a practical forecasting scenario. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12397 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Stochastic Predictive Analytics for Stocks in the Newsvendor Problem Pury, Pedro A. Applications Machine Learning 90B05, 90B90, 60J10, 62R07 This work addresses a key challenge in inventory management by developing a stochastic model that describes the dynamic distribution of inventory stock over time without assuming a specific demand distribution. Our model provides a flexible and applicable solution for situations with limited historical data and short-term predictions, making it well-suited for the Newsvendor problem. We evaluate our model's performance using real-world data from a large electronic marketplace, demonstrating its effectiveness in a practical forecasting scenario. |
| title | Stochastic Predictive Analytics for Stocks in the Newsvendor Problem |
| topic | Applications Machine Learning 90B05, 90B90, 60J10, 62R07 |
| url | https://arxiv.org/abs/2511.12397 |