First off, Welcome to Quantopian.
What you are asking is exactly what a typical algorithm does. One would first define the 'universe' of securities to trade within. This is typically decided by constraints on liquidity, type of security (ie only stocks and no ETFs), or some knowledge that a strategy performs well only on a specific group of securities (eg only works well on a specific sector). One can also set specific securities (eg AAPL IBM) but this has the inherent drawback of potential lookahead bias (why choose AAPL? Would we have chosen that stock 10 years ago when we start our backtest?) The 'universe' is typically defined in the pipeline and then set as a screen on the pipeline so only securities in the universe are returned.
The pipeline pulls together all the data one needs for their strategy. Rules can then be developed which use this data to determine what to buy and sell. One task which wasn't alluded to in the original post was how much to buy. Determining the weighting of stocks can be quite complex. If today we buy 10 stocks and tomorrow we buy 20 stocks, what should the algo do if there isn't enough money left in the portfolio to buy those stocks. The Quantopian platform will let you 'borrow' as much money as you wish. However, that won't match real life. The logic should rebalance existing positions to free up money for these new stocks or, alternately, cap the new stocks to only buy when there is a positive account balance.
Attached is a simple algo which is a start to what you are looking to do. Do take a look at the tutorials (https://www.quantopian.com/tutorials) especially part 2 on pipeline. That may give some better direction.
Good luck.
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