Here's an attempt at python/Quantopian. I'm an experienced C# developer but am a bit of a noob at python. My code is not very pythonic at this point, I've just gotten to the point where I can hack out an algo. It would be interesting to see if anyone can upgrade this algo to a more pythonic version. In particular the drawdown screening could be moved to a custom factor.
The strategy itself has promise, IMHO. It beats the market backtesting for the last five years. Results previous to the last five years are underwhelming, so it could use some work. Results in recent time are obviously important as market dynamics are changing.
The basic concepts used are ranking due to low price per earnings and price per book, with further screening based upon selecting stocks that have been exhibiting low drawdown.
It's pretty raw so watch out for bugs. Use at your own risk.
