I need to extract using API: Historical averages for 3yr PE, 5 Yr PE average basis a particular date (say what was the historical averages on the last quarter results date).
Similarly I need to know the FwdPE and Fwd PEG numbers on that particular date for a universe of stocks.
similarly for the following
Sector PE TTM
Industry PE TTM
Sector PEG TTM
Industry PEG TTM
Sector Price to Book TTM
Industry Price to Book TTM
Sector Return on Equity ROE
Industry Return on Equity ROE
Sector Return on Assets
Industry Return on Assets
Imagine I have a universe of stocks, and I am at the start of last quarter (say today’s date is 2025-09-30) and don’t know what’s coming ahead in terms of the results.
I want to extract the following :
1) Historical averages for 3yr PE (as of last quarter date), 5 Yr PE average for each of the stocks in my universe (say the stocks of NIFTY 100)
2) Similarly I need to know the FwdPE and Fwd PEG for each of the stocks in my universe (say the stocks of NIFTY 100)
Now, since the stocks of nifty 100 belong to different sectors and industries, I want to know the
- Sector PE TTM
- Industry PE TTM
- Sector PEG TTM
- Industry PEG TTM
- Sector Price to Book TTM
- Industry Price to Book TTM
- Sector Return on Equity ROE
- Industry Return on Equity ROE
- Sector Return on Assets
- Industry Return on Assets
As of same date i.e. start of last quarter (say today’s date is 2025-09-30)
Client has also shared
I am trying to use it the following way for example to get the FwdPe and FwdPEG.
import lseg.data as ld
tickerlist is the list of names from an index
forward_metrics= ['TR.FwdPE(SDate=2025-09-30)', 'TR.FwdPEG']
reqstd_forecasts=ld.get_data(
universe = tickerlist_str,
fields = forward_metrics,
parameters = {'Period':'FY1', 'Curn':'Native'})
reqstd_forecasts_metrics_mapping = {'Forward P/E (Daily Time Series Ratio)' :'Forecaster Estimates 1Y forward PE',
'Forward P/E/G (Daily Time Series Ratio)' : 'Forecaster Estimates 1Y forward PEG'