Like Quantopian, does Blueshift have a universe of US equities that I can refer to in my code? For example, Q1500US, Q500US, etc? Thank you
Hi Aaron,.unlike quantopian, our dataset track the S&P 500 historical members. So in itself it is a built-in universe - should be similar to Q500US. While I have not much clue on the exact rules on selecting Q500US, the S&P500 universe is a widely acceptable one with well-known methodologies.
That works for me. Thank you for responding so quickly.
can i use fetch csv to build my own universe?
At present we do not support uploading csv. On the other hand, we support multiple files strategy. So you can perhaps create a strateg filey named 'universe' and create a list of assets named 'my_custom_universe' as below:
my_custom_universe = ['KO','AAPL']
And then in your actual trading startegy you import the list. You can then use the imported list to create the universe for the strategy
from universe import my_custom_universe
def initialize(context):
context.universe = [symbol(ticker) for ticker in my_custom_universe]
I hope you plan to support fetch_csv in the future. This would be my strategy for ingesting a curated timeseries of tradable stocks. how dxo you propose to do fundamentals analysis. I assumed to not even try that inside a platform anymore and instead just generate a picklist externally, where I've already done the quantative fundamentals analysis on my own analytics service, and generated a picklist for the day.
what would your approach be for accessing external data then?