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- jerbouma/financetoolkit
jerbouma/financetoolkit
Transparent and Efficient Financial Analysis
RANKS FINANCE #6
AT A GLANCE
- LANGUAGE
- Python
- LICENSE
- MIT
- USAGE
- Use, change and redistribute, commercially too. Keep the notice.
- ACTIVITY
- last commit 6 days ago ()
- TOPICS
- algorithmic-trading
- equities
- factor-analysis
- finance
- financial-analysis
- financial-data
- financial-statements
- fundamental-analysis
- fundamentals
- market-data
- mcp-server
- performance-analysis
- HOMEPAGE
- https://www.jeroenbouma.com/projects/financetoolkit
- REPOSITORY
- GitHub ↗
- CATEGORY
- FINANCE
A summary, not legal advice.
README EXCERPT
While browsing a variety of websites, I repeatedly observed significant fluctuations in the same financial metric among different sources. Similarly, the reported financial statements often didn't line up, and there was limited information on the methodology used to calculate each metric. For example, Microsoft's Price-to-Earnings (PE) ratio on the 6th of May, 2023 is reported to be 28.93 (Stockopedia), 32.05 (Morningstar), 32.66 (Macrotrends), 33.09 (Finance Charts), 33.66 (Y Charts), 33.67 (Wall Street Journal), 33.80 (Yahoo Finance) and 34.4 (Companies Market Cap). All of these calculations are correct, however the method of calculation varies leading to different results. Therefore, collecting data from multiple sources can lead to wrong interpretation of the results given that one source could apply a different definition than another. And that is, if that definition is even available as often the underlying methods are hidden behind a paid subscription. This is why I designed the FinanceToolkit , this is an open-source toolkit in which all relevant financial methods (500+) are written down in the most simplistic way allowing for complete transparency of the method of calculat…
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TIMELINE
- Repository created
- Last push
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