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README.md: Add fecon235 for economics under Science #878

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@rsvp rsvp commented Apr 20, 2017

What is this Python project?

https://github.com/rsvp/fecon235 - Stars: 142 (as of 2017-04-20)

Python tools for financial economics. Code is demonstrated using Jupyter
notebooks for statistical computations and collection of raw data in
real-time. Extensive use of numpy, scipy, pandas, matplotlib especially
for time-series analysis and econometrics, yet the user interface is
very friendly.

API to access data include sources such as: U.S. Federal Reserve Bank,
Quandl, Yahoo and Google Finance.

Verify theoretical ideas and practical methods interactively

Here is a rendering of a Jupyter notebook for Housing economy, home prices and affordibility https://git.io/housing If you had executed that notebook locally, it would have also retrieved the latest available data and recomputed the results.

How is worker's wage correlated with GDP output? See https://git.io/gdpwage To score the Federal Reserve's performance under its dual mandate for inflation and unemployment, see https://git.io/fed (where tangentially the Phillips curve is discredited by constructing heat map scatter plots). Please see https://git.io/fedfunds to forecast the Fed Funds rate using futures contracts on LIBOR.

In https://git.io/gold we make a conjecture that real gold prices is a stationary time-series bound by real interest rates. In https://git.io/xbt we statistically analyze Bitcoin as a financial asset.

In https://git.io/equities we examine the separable components of total return for equities, especially due to enterprise earnings and market speculation, using S&P data assembled by Robert Shiller which goes back to the year 1871. In https://git.io/gdpspx we examine the close relationship between the real economy and the equities market, while demonstrating the Holt-Winters time-series model for predictions.

What's the difference between this Python project and similar ones?

We would recommend the Quantitative Economics site by Thomas Sargent for economists interested in theory, whereas fecon235 has a more data science emphasis with applications to finance. Thus the two projects are complementary.

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Anyone who agrees with this pull request could vote for it by adding a 馃憤 to it, and usually, the maintainer will merge it when votes reach 20.

Questions? Chat at https://gitter.im/rsvp/fecon235 Thank you for your consideration.

Python tools for financial economics. Code is demonstrated using Jupyter
notebooks for statistical computations and collection of raw data in
real-time.  Extensive use of numpy, scipy, pandas, matplotlib especially
for time-series analysis and econometrics, yet the user interface is
very friendly.

API to access data include sources such as: U.S. Federal Reserve Bank,
Quandl, Yahoo and Google Finance.

Serves to verify theoretical ideas and practical methods interactively.
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rsvp commented Apr 22, 2017

Wondering if a new heading, "Economics", should be introduced...

$ grep econo README.md 
* [fecon235](https://github.com/rsvp/fecon235) - Computational data tools for financial economics.
* [statsmodels](https://github.com/statsmodels/statsmodels) - Statistical modeling and econometrics in Python.

FYI grep for "finan" yields nothing except fecon235 so it's unique for "financial" and "finance".

@vinta vinta force-pushed the master branch 2 times, most recently from 23abd09 to 40cd98b Compare Jun 6, 2019
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stale bot commented Oct 30, 2019

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

@stale stale bot added the stale label Oct 30, 2019
@stale stale bot closed this Nov 6, 2019
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