daniel-st3/Daniel_Rodriguez_MSc_Thesis_Final
A machine learning pipeline analyzing how political bias in financial news amplifies retail investor sentiment and impacts stock market dynamics. Includes NLP feature engineering, time-series cross-validation, and reproducibility artifacts for S&P 500/NASDAQ tickers.
Stars
—
Forks
—
Language
Python
License
—
Category
Last pushed
Jan 20, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/daniel-st3/Daniel_Rodriguez_MSc_Thesis_Final"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
lefterisloukas/edgar-crawler
The only open-source toolkit that can download SEC EDGAR financial reports and extract textual...
yya518/FinBERT
A Pretrained BERT Model for Financial Communications. https://arxiv.org/abs/2006.08097
shirosaidev/stocksight
Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python...
Shubxam/Nifty-500-Live-Sentiment-Analysis
Live Sentiment Analysis dashboard of NIFTY 500 universe of stocks using plotly and streamlit
louisowen6/SENN
Code implementation of "SENN: Stock Ensemble-based Neural Network for Stock Market Prediction...