Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)

An Online Change Point Detection Algorithm Based on Difference-in-Differences for Time Series

Authors
Renjie Chu1, Yunxia Li1, *, Shijie Gao1
1Zhejiang University of Finance and Economics, Hangzhou, Zhejiang, 310018, China
*Corresponding author. Email: lyxmath@163.com
Corresponding Author
Yunxia Li
Available Online 20 February 2026.
DOI
10.2991/978-94-6463-992-6_4How to use a DOI?
Keywords
DID; online change point detection; AIC optimization; air quality
Abstract

Change point detection is widely used in various fields, such as finance and environmental monitoring, to identify significant shifts in the underlying state of the process under study. This paper introduces the Difference-in-Differences(DID) Online Change Point Detection(DOCPD) algorithm, which combines the DID method with a recursive refinement and the Akaike Information Criterion(AIC) optimization strategy for online change point detection in time series data. The algorithm enhances detection accuracy and robustness, and quantifies change point strength. Finally, real-world air quality data is used for empirical analysis. The results show that DOCPD algorithm can not only detect change points in complex scenarios, but also quantify the intensity of change points, providing insights for pollution management.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
20 February 2026
ISBN
978-94-6463-992-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-992-6_4How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Renjie Chu
AU  - Yunxia Li
AU  - Shijie Gao
PY  - 2026
DA  - 2026/02/20
TI  - An Online Change Point Detection Algorithm Based on Difference-in-Differences for Time Series
BT  - Proceedings of the 2025 4th International Conference on Mathematical Statistics and Economic Analysis (MSEA 2025)
PB  - Atlantis Press
SP  - 22
EP  - 28
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-992-6_4
DO  - 10.2991/978-94-6463-992-6_4
ID  - Chu2026
ER  -