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Datamule-python Alternatives
Similar projects and alternatives to datamule-python
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secsgml
A python package to parse Securities and Exchange Commission (SEC) Standardized Generalized Markup Language (SGML). Powers the datamule project.
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secfiler
Open sourcing filing compliance. Use at own risk. Part of the datamule project: https://datamule.xyz/resources#open_source.
datamule-python discussion
datamule-python reviews and mentions
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Show HN: I wrote an open source SEC filing compliance package
The U.S. Securities and Exchange Commission requires companies and individuals to submit data in SEC specific formats. Usually this means taking a columnar dataset and converting it to a specific XML schema.
In practice, this usually means paying a company for proprietary filing software that is annoying to use, and is not modifiable.
Here it an open source solution: https://github.com/john-friedman/secfiler
Note that this is a side project. My main project is manipulating SEC data. That project required me to figure out how to parse every SEC XML file into constituent tables. Since I had to do that, I might as well do the reverse -- which is how secfiler came about. The other project is https://github.com/john-friedman/datamule-python.
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New budget financial API, based on EDGAR data
Datamule (Package) GitHub: https://github.com/john-friedman/datamule-python
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Predicting good news using regulatory disclosure patterns, Python, SEC
I was curious if I could use insider trading patterns to predict whether the sentiment of 8-K filings were positive or negative.
https://github.com/john-friedman/datamule-python/blob/experimental/examples/predicting-good-news-from-insider-trading/exploration.ipynb
Doesn't look like it - not enough data. However, there is an interesting result. Trading behavior after a positive 8-K is very different for insiders. They wait to sell, possibly to let good news trickle out.
https://github.com/john-friedman/datamule-python/blob/experimental/examples/predicting-good-news-from-insider-trading/plots/sell-side.png
I'm considering looking at companies using their entire corpus of filings (e.g. 10-K to IRAN NOTICE) for a year and applying finbert for another try, but it seems expensive in terms of compute.
I've mostly solved the download problem by hosting my own SEC archive - it takes about 45 minutes to download 50,000 8-Ks and 150,000 Form 4s (1 year), but compute seems harder.
I used Loughran McDonald dictionaries to do the sentiment parsing - took about an hour, so I imagine applying finbert on a larger corpus would take weeks on my laptop.
Not sure if there's a better option?
- Discord bot for real-time SEC filing alerts with configurable filters
- A Python package for working with SEC filings at scale
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Show HN: OS SEC Chatbot with Artifacts
https://github.com/john-friedman/datamule-python
- Show HN: Package to parse SEC 10Ks into JSON and other fun things
- Download SEC filings quickly and without hassle
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Stats
john-friedman/datamule-python is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of datamule-python is Python.