Hey Ro,

So if you want to filter stocks by exchange you can use get_fundamentals but this will filter out ETFs. Check out my notebook here for examples on using get_fundamentals.

Check out the Pandas docs for information filtering DataFrames, the object that is returned by get_fundamentals and is used ubiquitously on Quantopian. Here is a good Pandas tutorial.

That all being said, we do enforce a limit on the number of securities in a universe. I'd recommend doing as much filtering as possible in get_fundamentals. An alternative is to use DollarVolumeUniverse which automatically gets the highest value securities by Dollar-Volume. Here are the docs for setting your universe

I hope that helps you get started!

@James Christopher I'm trying to do something similar, my desired algorithm has nothing to do with the state of the company, it is solely momentum based. How can I go about this using just percent increase? Additionally, would limiting the contents to a certain stock price range be possible?

Andrew

If you want to do a momentum based strategy the best I can recommend is to use the DollarVolumeUniverse I linked too above. Grab the price history for the securities price_histories = history(20, "1d", "price") and to get the momentum which we will define as: the latest price / the oldest price, you can iterate through your securities:

for security price_histories:  
    momentum = price_histories[security][-1] / price_histories[security][0]  

There are other ways to do this like applying the division to the whole dataframe, but this is a really good way to get started and see what is actually happening in a more "normal" context. Once you calculate the momentum you can store it or use it immediately.

I hope that helps. Check out these other momentum strategies (some are harder to follow than others):

Momentum Quick and dirty

Cross sectional momentum <=== more advanced

Good luck