Would someone help me with a rolling calculation for cumulative returns? In Excel this is simple but I'm having trouble figuring out how to do it with pandas. Hopefully the attached notebook will make it clear what I'm attempting to do.
TIA.
Would someone help me with a rolling calculation for cumulative returns? In Excel this is simple but I'm having trouble figuring out how to do it with pandas. Hopefully the attached notebook will make it clear what I'm attempting to do.
TIA.
There's probably a slicker way to do this but here's what worked for me:
for index in range(len(portfolio_index)-1):
portfolio_index[index+1] = portfolio_index[index] + (portfolio_index[index] * portfolio_daily_pct_change[index+1])
I don't know if this works for an entire portfolio, but if you want to calculate cumulative returns for a single security/index, this is a "slicker" way to do it:
from quantopian.research import symbols, returns
daily_returns = returns(
assets=symbols('YourSymbol'),
start='YourStartDate',
end='YourStartDate',
)
cumulative_returns = (1 + daily_returns).cumprod()