---
title: "International Journal of Forecasting: recent papers"
description: "International Journal of Forecasting published 6 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #117 of 239 journals."
url: https://scholar4ai.com/journals/international-journal-of-forecasting
markdown_url: https://scholar4ai.com/journals/international-journal-of-forecasting.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "International Journal of Forecasting published 6 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #117 of 239 journals."
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-10-26T14:52:47+09:00
window: 2026-09-27 to 2026-10-26
source: OpenAlex (CC0)
---

# International Journal of Forecasting

- 0 papers in the last 7 days
- category: Economics
- publisher: Elsevier BV
- ISSN 0169-2070

Back to the ranking: https://scholar4ai.com/rankings/journals.md

## Key findings

- International Journal of Forecasting published 6 papers in the last 30 days (2026-09-27 to 2026-10-26), ranking #117 of 239 journals.
- Leading institutions: Bank of Lithuania (1), Vrije Universiteit Amsterdam (1) and Aarhus University (1).
- Countries: China (2), Lithuania (1) and Denmark (1).
- From Oct 2023 to Sep 2026, International Journal of Forecasting published 265 papers (7 a month on average, by publication date in OpenAlex).
- Its most frequent keywords over that period were “forecast accuracy” (31), “probabilistic forecasting” (18) and “out-of-sample forecasting” (16).
- Its most-cited paper of the period is “Deep learning and NLP in cryptocurrency forecasting: Integrating financial, blockchain, and social media data” (2025-03-18), with 29 citations.

## The last 36 months

*Papers by publication date, Oct 2023 to Sep 2026*

| Oct 23–Sep 24 | Oct 24–Sep 25 | Oct 25–Sep 26 | 36 months |
|---:|---:|---:|---:|
| 94 | 88 | 83 | 265 |

*Most frequent keywords, Oct 2023 to Sep 2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | forecast accuracy | 31 |
| 2 | probabilistic forecasting | 18 |
| 3 | out-of-sample forecasting | 16 |
| 4 | macroeconomic forecasting | 14 |
| 5 | forecast combination | 13 |
| 6 | inflation forecasting | 11 |
| 7 | time series forecasting | 10 |
| 8 | forecast evaluation | 9 |
| 9 | forecast reconciliation | 8 |
| 10 | nowcasting | 8 |

*Most-cited papers published Oct 2023 to Sep 2026*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 29 | 1.5 | [Deep learning and NLP in cryptocurrency forecasting: Integrating financial, blockchain, and social media data](https://doi.org/10.1016/j.ijforecast.2025.02.007) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2025-03-18 | Vincent Gurgul, Stefan Lessmann, Wolfgang Karl Härdle |
| 2 | 19 | 1.0 | [Forecasting macroeconomic data with Bayesian VARs: Sparse or dense? It depends!](https://doi.org/10.1016/j.ijforecast.2025.02.001) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2025-02-26 | Luis Gruber, Gregor Kastner |
| 3 | 17 | 0.9 | [Predicting inflation with recurrent neural networks](https://doi.org/10.1016/j.ijforecast.2024.07.010) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2025-03-01 | Livia Paranhos |
| 4 | 9 | 0.5 | [On forecast stability](https://doi.org/10.1016/j.ijforecast.2025.01.006) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2025-02-25 | Rakshitha Godahewa, Christoph Bergmeir, Zeynep Erkin Baz et al. |
| 5 | 8 | 0.4 | [Hierarchical neural additive models for interpretable demand forecasts](https://doi.org/10.1016/j.ijforecast.2025.03.003) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | 2025-04-30 | Leif Feddersen, Catherine Cleophas |

*Papers, newest first.*

| Date | Title | Journal | Authors | Affiliations |
|---|---|---|---|---|
| 2026-10-01 | [The effect of new housing supply in structural models: A forecasting performance evaluation](https://doi.org/10.1016/j.ijforecast.2026.09.008) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Stefan Girstmair | Bank of Lithuania |
| 2026-10-01 | [Long-lead forecasting of El Niño–Southern Oscillation using score-driven models with many predictors](https://doi.org/10.1016/j.ijforecast.2026.09.009) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Janneke van Brummelen, Sebastian Jensen, Siem Jan Koopman et al. | Aarhus University; Vrije Universiteit Amsterdam; Barcelona Institute for Global Health |
| 2026-10-01 | [Integration of joint energy commodity price forecasts with hydrogen energy system planning under uncertain climate policies](https://doi.org/10.1016/j.ijforecast.2026.05.005) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Hongtao Ren, Caiyu Chen, Li Su et al. | East China University of Science and Technology; Renmin University of China; China Construction Bank; … |
| 2026-10-01 | [High-dimensional portfolio optimization with weight constraints: Forecasting models utilizing GARCH-EVT, R-vine copula, and SCAD penalty](https://doi.org/10.1016/j.ijforecast.2026.08.007) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Jian Lv, Chenxu Wang, Wenyong Yuan | Zhejiang University of Finance and Economics |
| 2026-10-01 | [Adaptive Bayesian very short-term wind power forecasting based on the generalised logit transformation](https://doi.org/10.1016/j.ijforecast.2026.08.002) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Tao Shen, Jethro Browell, Daniela Castro‐Camilo |  |
| 2026-10-01 | [Combining value-at-risk and expected-shortfall forecasts via the model confidence set](https://doi.org/10.1016/j.ijforecast.2026.09.011) | [International Journal of Forecasting](https://scholar4ai.com/journals/international-journal-of-forecasting.md) | Alessandra Amendola, Vincenzo Candila, Antonio Naimoli et al. |  |

## Cite this page

Scholar4AI. (2026). International Journal of Forecasting. Journal Research Rankings. Retrieved October 26, 2026, from https://scholar4ai.com/journals/international-journal-of-forecasting

```bibtex
@misc{scholar4ai-journals-international-journal-of-forecasting,
  author = {{Scholar4AI}},
  title = {International Journal of Forecasting},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/journals/international-journal-of-forecasting}},
  urldate = {2026-10-26},
  note = {Journal Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).