Api question: what is universe

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posted May 15, 2015

I am very confused with universe in Help doc. In Help docs I find there are 3 methods can change universe:

set_universe(sids)

update_universe(sids)

fetch_csv(url, pre_func=None, post_func=None, universe_func, date_column='date',  
           date_format='%m/%d/%y', timezone='UTC', symbol=None, mask=True, **kwargs)

(1) set_universe, 200 limit, in initialize() method.

(2) update_universe, it seems no limit, only if we update in different time. In before_trading_start() method.

(3) fetch_csv, 200 limit, in initialize() method.

So my guess is:

(1) if we only use set_universe or fetch_csv, then universe have a cap of 200.

(2) if we use update_universe, then universe size will grow, it records all the securities we have updated. Then in handle_data(context, data), we can see all the securities we have updated, even they are not in our position or order now.

Is my understanding right?

6 responses

Alisa Deychman

May 15, 2015

Hi Jian,

"Universe" is the entire collection of securities that your algorithm can trade. There are 4 ways to create your stock universe:

Manually using the sid(), symbol(), or symbols() methods. The SID is a unique identifier on Quantopian for each stock. Symbol() lets you look up a single ticker to trade. Symbols() lets you pass a list of tickers to trade.
set_universe() is a random basket of stocks, based on their traded dollar volume. This reduces the bias introduced by manually hand-picking stocks. This universe of stocks gets updated automatically each quarter, as the dollar volume changes.
Fetcher allows you to import data in a CSV to your algorithm. You can import stocks to create your universe, or you can import other data, as a signal to trade upon.
Fundamental data can be used in before_trading_start(). You can query an unlimited number of stocks and filter down based on some criteria (market cap, P/E ratio, etc). You then limit the query to return a maximum of 200 tradeable stocks. You can then use the function update_universe() to update your universe of stocks each day to your criteria is always met.

In all 4 of these cases, you can trade up to 200 securities in your algorithm. So you can either manually enter 200 tickers, set a 2% universe (roughly 160 stocks), have up to 200 stocks per day in your CSV, or use fundamentals to filter down 200 stocks based on value metrics.

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Jian Jiao

May 15, 2015

Thank you for this detailed answer Alisa!

Grant Kiehne

May 17, 2015

I can't put my fingers on the link where I showed it, but in practice, using update_universe(), more than 200 stocks can be traded, but only 200 new securities can be added per trading day. --Grant

Blue Seahawk

May 17, 2015

https://www.quantopian.com/posts/how-to-create-a-symbol-from-string#54f5f2248be13134f2000027 demonstrates that (using get_fundamentals). I saw an algo trading over 1400 stocks once. Note too Jian, if you print len(data), you'll probably find that the count is not always what you might expect, because, for a bar where a stock does not trade, it won't be present. Meanwhile a stock can be absent from data yet present in context.portfolio.positions (plus number of shares, amount, can be zero there). One other thing to keep in mind wrt what the data object contains, is that if you use fetcher, it adds string keys to data.

Jian Jiao

May 17, 2015

Great discovery, Thank you Grant and garyha!

Grant Kiehne

May 17, 2015

Just keep in mind that Q doesn't really support trading of large portfolios. Watch out for the 50-second time out of a call to handle_data(), which will crash the algo. Also, there is a finite amount of memory available (there's no way to tell how much has been allocated to the algo and how much has been used). You might consider the Q research platform, if you need more flexibility (although you'll still have to deal with an unknown amount of memory allocated, that could be exceeded).

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