Hi there, I am using a combination of the Eikon API and the RDP API, in Python on a Mac (Ventura). I am searching for all deals relating to the following ISINS (['BRJBSSACNOR8', 'BRMRFGACNOR0', 'BRBEEFACNOR6']) and would like to eventually map these to the ultimate parent of each bank that participated in each deal. From the Data Library, it seems not possible to return a PermID, RIC, or ISIN for the managers on a deal. Therefore, I need to search them by name to find either a) their ultimate parents directly or b) their ISIN, RIC, or PermID, which I can then search for their ultimate parents. Are you able to help me do this with either RDP or Eikon API? Thanks in advance for any help.
import pandas as pd import eikon as ek import refinitiv.data as rd isins = ['BRJBSSACNOR8', 'BRMRFGACNOR0', 'BRBEEFACNOR6'] # convert ISINs to PermIDs to search deal screener permids = ek.get_symbology(isins, from_symbol_type='ISIN', to_symbol_type='OAPermID permids = ','.join(permids['OAPermID']) # pulling loans data fields = ["TR.LNSdcDealNum,TR.LNSDCTrancheId,TR.LNAnnouncementDate,TR.LNTrancheClosingDatePrint,TR.LNMaturityDate,TR.LNFinalMaturityDate,TR.LNIssuerUltParent,TR.LNIssuerUltParentPERMID,TR.LNIssuerUltParentNation,TR.LNIssuerUltParentSubRegion,TR.LNIssuer,TR.LNIssuerSDCCusip,TR.LNIssuerPERMID,TR.LNIssuerNation,TR.LNIssuerSubRegion,TR.LNTotalFacilityAmount(Scale=6),TR.LNTrancheAmount(Scale=6,Curn=USD),TR.LNOriginalTrancheCurrency,TR.LNTargetMarketNation,TR.LNUseOfProceeds(Concat='|'),TR.LNTrancheType,TR.LNYieldType,TR.LNStatusOfLoan,TR.LNBookRunnerParentCount,TR.LNLeadCoLeadIntCoManagerCount,TR.LNIsBookRunner(Concat='|'),TR.LNManagerRole(Concat='|'),TR.LNLeadCoLeadIntCoManagerLong(Concat='|'),TR.LNLeadCoLeadIntCoManagerParentLong(Concat='|'),TR.LNPrincipalAmountPerBookRunnerThisMarket(Scale=6),TR.LNCommitmentAmount(Scale=6,Curn=USD,Concat='|')"] df_loans,e = ek.get_data("SCREEN(U(IN(DEALS)/*UNV:DEALSLOAN*/),IN(TR.LNParticipant(LNPartRole=LNBUP)," + permids + "))", fields, {"Curn":"USD"}) # find unique parents unique_names = df_loans['Book, Co-Manager, Participant Parent (Full Name)'].str.split('|').explode().unique() df_unique_names = pd.DataFrame(unique_names, columns=['Unique Names']) ## next step - find ultimate parents of each of these unique parents??