https://github.com/gyund/fundamental-analysis

Aggregate and modularize efficient and reliable tools for performing fundamental analysis on US securities
https://github.com/gyund/fundamental-analysis

fundamental-analysis python3 sec-edgar stock-market stocks

Last synced: 8 days ago
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Aggregate and modularize efficient and reliable tools for performing fundamental analysis on US securities

• Host: GitHub
• URL: https://github.com/gyund/fundamental-analysis
• Owner: gyund
• License: epl-2.0
• Created: 2023-04-17T23:45:00.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-12T03:07:33.000Z (5 months ago)
• Last Synced: 2024-12-21T23:10:15.049Z (17 days ago)
• Topics: fundamental-analysis, python3, sec-edgar, stock-market, stocks
• Language: Python
• Homepage: https://gyund.github.io/fundamental-analysis/
• Size: 2.31 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 37
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Codeowners: .github/CODEOWNERS
  • Security: SECURITY.md

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# StockTracer

**Stock Analysis Framework**

The goal of this project is aggregate a variety of ways to consume information about a particular equity traded on the US stock market and provide a modular mechanism to process it. Core tenants of this project include:

- **Heavy data caching** - don't download static data more than once

- **Efficient use of storage** - leave data compressed while not in use

- **Batch Processing** - We can't store all information in memory, so break problems up

- **Speed** - Find and avoid bottlenecks of big data processing

## Requirements

- `python 3.10+`

## Getting Started

### Users

```sh

# basic install

pip install stocktracer

# with tensorflow dependencies for analysis modules

pip install stocktracer[tensorflow]

# Perform analysis

stocktracer analyze --tickers aapl,msft > report.txt

# Help

stocktracer

```

For development guides, see our [documentation](https://gyund.github.io/fundamental-analysis/getting-started)

## Disclaimer

This project seeks to use publicly available information to perform security analysis and

help perform long term risk analysis. Results provided from this project are generally for 

academic use only and are not considered advice or recommendations. This project makes no

performance claims or guarantees. Please read the [license](LICENSE) 

for this project. Usage of any data is at your own risk.