Python API Assistance Needed: Retrieve Option RIC from Underlying, Strike, and Maturity

HarveySaldana

Hi Team,

I'm assisting a client who is looking to retrieve the 6-month ATM implied volatility (bid/ask/mid) for an option using Python API access.

The client currently has the following inputs available:

• Underlying stock RIC
• Option strike
• Option maturity/expiry date

One challenge is that the underlying RIC may correspond to a specific exchange, while the relevant option may be listed on a different exchange.

I initially suggested the use of ATM IV RICs (e.g., AAPLATMIV.U) and relevant fields for 30D/60D/90D ATM implied volatility, along with the ETIVOLSURF and IMPLIEDVOL pages. However, after discussing further with the client, their main requirement is to determine whether there is a way to programmatically identify the correct option RIC(s) using only:

• Underlying RIC
• Strike
• Maturity

Specifically, the client would like to automate this workflow in Python and avoid manually searching for the option RIC.

Could you please advise:

1. Is there an API workflow or content set that can be used to discover the option RIC from the above parameters?
2. Is there a recommended way to retrieve the corresponding ATM volatility (including bid/ask/mid, if available) once the option contract has been identified?
3. Are there any examples or documentation available for this use case?

Any guidance or sample code would be greatly appreciated.

ujjawal_khandelwal

Hi @HarveySaldana,
Thank you for your question!
There are a couple of great ways to approach this. Let me walk you through what I'd recommend.

STEP 1:

The cleanest starting point is the Advanced Search (AS) app on Workspace, combined with the Search function in the LSEG Data Library for Python.

In Workspace:

1. Open Advanced Search
2. Set Universe Builder → Equity & Index Derivatives → Options
3. Add filters: Underlying RIC, Expiry Date, Strike Price, etc.
4. Hit Export Query → Codebook → Copy Code

The exported code uses the older refinitiv.data library - I'd recommend updating it to the current lseg.data library as shown below.

import lseg.data as ld

ld.open_session()


options = ld.discovery.search(

    view=ld.discovery.Views.EQUITY_QUOTES,

    top=10,

    filter=(

        "SearchAllCategoryv2 eq 'Options'"

        " and UnderlyingQuoteRIC eq 'AAPL.O'"

        " and StrikePrice gt 340"

        " and ExpiryDate ge 2026-10-23"

    ),

    select="DTSubjectName, AssetState, SearchAllCategory, ExchangeName, "

           "CallPutOption, StrikePrice, ExpiryDate, RIC, "

           "UnderlyingQuoteRIC, UnderlyingRCSAssetCategoryLeaf"

)

display(options)

Step 2 - Retrieve the Data

Once you have the RICs, a simple get_data() call gets you what you need:

I'm not 100% certain of the right field names for your specific case. I'd recommend either:

Using Data Item Browser (DIB) on Workspace - search your option RIC and browse the available fields or raising a Content Query with LSEG Support - they'll point you to the exact fields for your instrument type

df = ld.get_data(

    universe=[options['RIC'][0]],

    fields=['BID', 'ASK', 'MID_PRICE', 'TR.IMPLIEDVOLATILITY', 'STRIKE_PRC', 'EXPIR_DATE']

)

display(df)

Useful Resources

To get more control over your search queries and data retrieval, these are well worth going through:

• Accelerating Search: Unlocking the Power of Property Exploration
• Building Search into your Application Workflow
• Historical Implied Volatility and Greeks of Index Options 'At The Money' On Update and in the Past using Python Type Hints Part 1
• LSEG Data Library - Patterns and Features - Series Index

Please let me know if this helps. Thank you : )
- Ujjawal Khandelwal