How to integrate ESG data into investment decisions

c.xue
Newcomer
Hi,
I am reading the research article: How to integrate ESG data into investment decisions.
I do not understand:
df,err = ek.get_data('{}{}({}-01-01)'.format('0#', index, year), fields=['TR.TRESGScore'], parameters={'SDate': '{}-01-01'.format(year), 'Period': 'FY0'})
We do not define the "year" before. How to understand the year in this code? When I run the code, python reports errors.
Thanks
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Best Answer
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Hi @c.xue
The full source for the above article is available as a notebook at Example.EikonAPI.Python.DiversityAndInclusion - as per the link at the top and bottom of the article
The code snippet you quote above is actually from a function in the above notebook:
def getDataForYear(year):
display('Getting data for: {}'.format(year))
# get index constituents at the begining year
df,err = ek.get_data('{}{}({}-01-01)'.format('0#', index, year), fields=['TR.TRESGScore'], parameters={'SDate': '{}-01-01'.format(year), 'Period': 'FY0'})
# filter out the instruments based on ESG ratings
subset = getSubset(df)
# get the performance data for this subset
df2,err = ek.get_data(subset, fields=['TR.CLOSEPRICE.date', 'TR.CLOSEPRICE'], parameters={'SDate': '{}-01-01'.format(year), 'EDate': '{}-01-01'.format(year + 1), 'Frq':'CQ'})
df2 = df2.dropna()
# consolidate the price data for instruments
alphaList = []
ser = df2['Date'].value_counts()
for x in ser[ser > 5].index:
ser = df2.loc[df2['Date'] == x].sum()
alphaList.append({'Date': x, 'Close Price': ser['Close Price']})
return alphaList0
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