Hi, my name is Eugenio and I'm a beginner here at Quantopian. I would like to try to implement some etf rotation strategy from scratch, but following some expert template (Frank Grossmann for example). This becouse my hope is to find some interesting algo and learning all what I can in the meantime.
The first issue I came up with is the data.
# Research environment functions
from quantopian.research import prices, symbols
# Pandas library: https://pandas.pydata.org/
import pandas as pd
# Query historical pricing data for SPY
spy_close = prices(
assets=symbols('SPY'),
start='2018-01-01',
end='2018-12-31',
)
# Combine results into a pandas DataFrame and plot
pd.DataFrame({
'SPY': spy_close,
}).plot(
title='SPY Close Price '
);With this code I download spy closing data for the 2018 and plot them.
?What I should do if I want to save the data in a csv file?
(in that way I can make comparison with data from other sources)
?Those data are still not adjusted for split and dividends as Frank stated in this post?
wrong etf rankings
I have here
link
a csv file that I downloaded from tiingo and manually adjusted.
?It is possible to load and work on data I have on csv like this?
These are for the moment the question I have, tnx for Your time and
best regards
Eugenio
