Using rdp.get_option_analytics - what is the Parameter to get prices from other Contributors?
Client's full script is below and right now it gets prices from our Composite RIC CLP=
But what client wants to add in this script is to be able to add a parameter where he can specify a particular contributor, e.g. Central Bank of Chile - RIC CLPOB= - Please advise how to achieve this. Thank you.
import pandas as pd
import refinitiv.dataplatform as rdp
from refinitiv.dataplatform.content import ipa
from refinitiv.dataplatform.content.ipa import option
rdp.open_desktop_session('### YOUR APP KEY ###')
pd.set_option('display.max_columns', 100)
##############CAMBIAR FECHA##############
FECHA_CIERRE = "2023-03-13"
df = rdp.get_option_analytics(
universe = [option.Definition(
underlying_type=option.UnderlyingType.FX,
underlying_definition='USDCLP',
strike=760.0,
call_put="Call",
exercise_style = "Euro",
notional_amount=1000,
notional_ccy="USD",
buy_sell="buy",
end_date='2023-03-20',
),
option.Definition(
underlying_type=option.UnderlyingType.FX,
underlying_definition="USDCLP",
strike=760.0,
call_put="Put",
exercise_style = "Euro",
notional_amount=250000,
notional_ccy="USD",
buy_sell="sell",
end_date='2023-03-20'
)],
calculation_params = option.CalculationParams(
valuation_date=FECHA_CIERRE,
pricing_model_type = ipa.enum_types.PricingModelType.BLACK_SCHOLES
),
# fields = ["ValuationDate","OptionType","ExerciseType","ExerciseStyle","EndDate",
# "StrikePrice","DealCcy","UnderlyingCcy","MarketValueInDealCcy","VolatilityPercent","DeltaPercent","GammaPercent", "InstrumentDescription"]
)
df['DeltaUSD'] = df['DeltaPercent']*df['NotionalAmount']/100
df['GammaUSD'] = df['GammaPercent']/100*1000000
df['VegaUSD'] = df['VegaPercent']/100*1000000
df['ThetaUSD'] = df['ThetaPercent']/100*1000000
df['PriceCLP'] = abs(df['MarketValueInDomesticCcy']/df['NotionalAmount'])
df['ImpliedVolatilityPercentf'] = df['ImpliedVolatilityPercent']
df['DomesticDepositRatePercentf'] = df['DomesticDepositRatePercent']
df['ForeignDepositRatePercentf'] = df['ForeignDepositRatePercent']
df['InstrumentDescriptionf'] = df['InstrumentDescription']
df['ValuationDatef'] = df['ValuationDate']
df
