Questions regarding the fiscal year

Currently, we use the Python API and ld.get_data() to extract fundamental and ESG data of several companies over time. We want to make sure that the date variables we are using in both requests (see below) correspond to the last day of the company’s business year so that we can interprete both datasets on a fiscal year level.
Therefore, we have the following questions:
Is it true that 'TR.F.PeriodEndDate' equals the last day of the company's business year?
Is it true that date variables of a specific variable (as for example 'TR.TRESGScore.date' for 'TR.TRESGScore') equals the variable 'TR.F.PeriodEndDate'?
Is it true that date variables of a specific variable (as for example 'TR.F.TOTASSETS.date' for 'TR.F.TOTASSETS') equals the variable 'TR.F.PeriodEndDate'?
Is there an additional possibility to get the fiscal year for yearly company observations?
Code:
# Extracting the data
ld.open_session()
DJ_constitutents_2024_06_14_df = ld.get_data(
universe=[
'.DJI'
],
fields=[
'TR.IndexConstituentRIC'
],
header_type=HeaderType.TITLE,
parameters = {
'SDate':'2024-06-14',
'EDate':'2024-06-14',}
)
ld.close_session()
RIC_list = DJ_constitutents_2024_06_14_df['Constituent RIC'].tolist()
fundamental_variables_list = [
# Date item
'TR.F.PeriodEndDate',
'TR.F.TOTASSETS.date',
# Main items
'TR.F.TOTASSETS',
'TR.F.TOTCURRASSETS',
]
ld.open_session()
fundamental_df = ld.get_data(
universe=RIC_list,
fields=fundamental_variables_list,
parameters={'SDate':'0','EDate':'-16','Frq':'FY', 'Curn': 'USD'},
header_type=HeaderType.NAME
)
ld.close_session()
ESG_variables_list = [
#date
'TR.TRESGScore.date',
#score
'TR.TRESGScore',
'TR.TRESGCScore',
]
# Extracting the data
ld.open_session()
ESG_df = ld.get_data(
universe=RIC_list,
fields=ESG_variables_list,
parameters={'SDate':'0','EDate':'-16','Frq':'FY'},
header_type=HeaderType.NAME
)
ld.close_session()
Answers
-
Thank you for reaching out to us.
This forum is dedicated to software developers using LSEG APIs. The moderators on this forum do not have deep expertise in every bit of content available through LSEG products, which is required to answer content questions such as this one.
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