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Looking for simple code to return daily percent change using similar code below - is there an easy function similar to get_pricing()?

symbol = ["UAL","IBM"]
start = "2019-01-02"
end = "2020-10-16"
start_1 = "2019-01-01"
end_1 = "2020-10-15"
prices = get_pricing(symbol, start_date=start, end_date=end, fields="price")
if isinstance(symbol, list):
prices.columns = map(lambda x: x.symbol, prices.columns)
else:
prices.name = symbol

2 responses

There are two functions for getting returns similar to get_pricing. These are returns and log_returns and can be used within notebooks (and not algos). There is documentation on them here and here. So, something like this will work

# First need to import the pricing and returns functions  
from quantopian.research import get_pricing, returns, log_returns

# Set parameters  
symbol = ["UAL","IBM"]

start = "2019-01-02"  
end = "2020-10-16"

# Get prices and returns  
prices = get_pricing(symbol, start_date=start, end_date=end, fields="price")  
returns_1_day = returns(symbol, start=start, end=end, periods=1, price_field='price')  
log_returns_1_day = log_returns(symbol, start=start, end=end, periods=1, price_field='price')

Attached is a notebook showing this in action. Good luck!

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thanks!