Code is to extract implied volatility data for multiple stocks/indices from Equity Volatility Sur...

...face

Hi, Below code is to extract implied volatility data for SP500 index. However, I want to pull data for multiple stocks and indices for multiple time horizon using single run. How can I amend the code to do that?

import refinitiv.data as rd

from refinitiv.data.content.ipa import surfaces

import pandas as pd

import plotly.express as px

import plotly.graph_objects as go

rd.open_session()

request_definition = rd.delivery.endpoint_request.Definition(

url="https://api.refinitiv.com/data/quantitative-analytics-curves-and-surfaces/v1/surfaces",

method=rd.delivery.endpoint_request.RequestMethod.POST,

body_parameters={

"universe": [

{

"surfaceTag": "SPX",

"underlyingType": "Eti",

"underlyingDefinition": {

"instrumentCode": ".SPX@RIC"

},

"surfaceParameters": {

"inputVolatilityType": "Quoted",

"timeStamp": "Default",

"priceSide": "Mid",

"volatilityModel": "SSVI",

"xAxis": "Tenor",

"yAxis": "Moneyness",

"calculationDate": "2024-03-21"

},

"surfaceLayout": {

"format": "Matrix",

}

}],

"outputs": ["Data", "ForwardCurve", "MoneynessStrike"]

}

)

response = request_definition.get_data()

surface_tag = response.data.raw['data'][0]['surfaceTag']

_surface_df = pd.DataFrame(

data=response.data.raw['data'][0]['surface'])

surface_df_title = f"{surface_tag} Equity Volatility Surface"

surface_df = pd.DataFrame(

data=_surface_df.loc[1:,1:].values,

index=_surface_df[0][1:],

columns=_surface_df.iloc[0][1:])

surface_df.columns.name = "Moneyness"

surface_df.index.name = "Tenor"

surface_df.loc[["3M","6M"],["1"]]