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fecon235
Jupyter notebooks for financial economics and risk analysis
What it is
A collection of Python-based Jupyter notebooks for financial economics, offering high-level access to free data sources such as FRED, Quandl, and pandas_datareader for stocks, funds, ETFs, and futures. The notebooks handle data retrieval and munging, econometric and time-series analysis, portfolio mathematics, and visualization, including Gaussian mixture modeling of leptokurtotic risk and adaptive Boltzmann portfolios. They suit researchers and economists who want reproducible, interactive analysis in a notebook or Python console. Much of the underlying code has been refactored into a separate repository, fecon236, so users of the computational modules will need to consult that project as well.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Strategy research, Data analysis |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): 0 over the period, now 1,279. Gaps mean no snapshot was taken that day.
Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.
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