Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market

By Mingxuan Yi, Vidal Mehra, Jing Chen, John Cartlidge

Published 2026-08-02

Everscope rating

1764

Relevance to quantitative trading

8 / 10

Implementation complexity

6 / 10

Reproducibility

4 / 5

About this paper

Methodology: Text-Enhanced Regime Shift Detection Pipeline with Bidirectional Cross-Modal Validation. Problem types: Anomaly Detection, Time Series Classification, Natural Language Processing, Causal Inference, Risk Management.

arXiv:2605.30363 · Code · Paper rankings

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