Official code for ''RAG Meets Temporal Graphs: Time-Sensitive Modeling and Retrieval for Evolving Knowledge''.
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Updated
Feb 25, 2026 - Python
Official code for ''RAG Meets Temporal Graphs: Time-Sensitive Modeling and Retrieval for Evolving Knowledge''.
Research pipeline for building a daily Market Criticism Index and studying its relationship with US market outcomes.
📈 Analyze press releases to predict earnings announcement returns using structured data and natural language processing techniques.
End-to-End Python implementation of Wu et al.'s (2025) ICAIF'25 paper. It translates unstructured earnings press releases into quantifiable market signals. Implements oLDA topic modeling, Transformer embeddings (BERT/FinBERT/MPNET), GPT-4o interpretability, and rigorous econometric analysis.
A custom spaCy-based Named Entity Recognition (NER) model designed for financial texts, capable of identifying companies, stock symbols, market indexes, and stock exchanges for use in news analytics and trading insights.
Online supplement and reproducibility materials for a nested benchmark evaluation of cross-source orientation distance and post-filing risk.
Source-available annual report NLP and event-study pipeline for research
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