---
title: Machine learning framework for forecasting sales of new products with short life cycles
url: https://www.ml-quant.com/papers/repec/eee-intfor-v-39-y-2023-i-4-p-1874-1894/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:intfor:v:39:y:2023:i:4:p:1874-1894
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207022001364%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A39%3Ay%3A2023%3Ai%3A4%3Ap%3A1874-1894
featured: 2023-10-12
citations: unknown
topic: Econometrics & Forecasting
---


# Machine learning framework for forecasting sales of new products with short life cycles

For predicting sales of short-lived products, simple ARIMAX is more effective than deep neural networks, but DNNs perform well when Gaussian white noise is added, a study finds.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169207022001364%3Bh%3Drepec%3Aeee%3Aintfor%3Av%3A39%3Ay%3A2023%3Ai%3A4%3Ap%3A1874-1894
- Identifier: RePEc:eee:intfor:v:39:y:2023:i:4:p:1874-1894
- Released: 2023-10-12
- First featured: Quant Letter No. 20 (2023-10-12): https://www.ml-quant.com/issues/2023-10-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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