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arXiv · 2508.15369

Enhancing Forecasting with a 2D Time Series Approach for Cohort-Based Data

Yonathan Guttel·Orit Moradov·Nachi Lieder·Asnat Greenstein-Messica
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Abstract

This paper introduces a novel two-dimensional (2D) time series forecasting model that integrates cohort behavior over time, addressing challenges in small data environments. We demonstrate its efficacy using multiple real-world datasets, showcasing superior performance in accuracy and adaptability compared to reference models. The approach offers valuable insights for strategic decision-making across industries facing financial and marketing forecasting challenges.

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Yonathan Guttel, Orit Moradov, Nachi Lieder, Asnat Greenstein-Messica. 2025-08-21. Enhancing Forecasting with a 2D Time Series Approach for Cohort-Based Data. https://doi.org/10.1109/cifercompanion65204.2025.10980398

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