I've been investing for the last 15 years in a weird Buffett/Soros way. For the last few years I've been toying with the idea of modeling myself.

I want to build a 'stock screener' that will be able to suggest stocks based on:

  • 13F (like Buffett).
  • Stock repurchase.
  • Inside trading.
  • Expectations.
  • Falling angels score.
  • EV / EBIT.
  • Company events (ceo left, class action, ..)

Is there an existing framework that I can use to allow me to achieve this? I'm a Python programmer (dayjob)


EDIT: I found this book- Systematic Trading: A unique new method for designing trading and investing systems that also comes with the python project. I'm reading the book, so far looks promising

  • $\begingroup$ You might start (if you have not already done so) by investigating the capabilities of commercially available stock screeners such as Zacks Investment Research, FactSet or Refinitiv's QA Direct. $\endgroup$
    – Alex C
    Jun 26, 2019 at 0:43

1 Answer 1


Given you have a database that stores this data daily, you could write a short python script to apply your screening and email you the daily rankings or scores.

I think you can even do this in Excell if you have a Bloomberg or TR terminal. I am pretty sure that you can.

If you want to backtest the performance of such a strategy then I think using Quantopians platform is the best and easiest way to go.


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