franciscogmm/FinancialAnalysisUsingNLPandMachineLearning
Used text analytics (NLP) and machine learning to determine the true earnings quality of publicly listed companies
This helps financial analysts and investors assess the true financial health of publicly traded companies. It takes a company's Proxy Statement Compensation Discussion and Analysis (CD&A) as input and provides an assessment of their earnings quality (high or low). Financial professionals who analyze company reports and financial statements would use this.
No commits in the last 6 months.
Use this if you want to analyze the sentiment and content of a company's Compensation Discussion and Analysis to gain deeper insights into their reported earnings quality.
Not ideal if you are looking for a tool to predict stock prices or to analyze financial statements directly without considering the qualitative text.
Stars
18
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 04, 2017
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/franciscogmm/FinancialAnalysisUsingNLPandMachineLearning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Shubxam/Nifty-500-Live-Sentiment-Analysis
Live Sentiment Analysis dashboard of NIFTY 500 universe of stocks using plotly and streamlit
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...
louisowen6/SENN
Code implementation of "SENN: Stock Ensemble-based Neural Network for Stock Market Prediction...