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How to efficiently pull historical options analytics (PCR, Risk Reversals) natively for equity RICs?

Xovizo

Hi everyone,

I am currently finalizing the architecture for a 10-year quantitative equity options backtest using the Refinitiv Data API (refinitiv.data in Python). To complete our data pipeline, we need to extract a specific set of point-in-time historical options analytics for a custom universe of US equities.

Specifically, we are looking to retrieve the following daily historical data points for the underlying equity RICs over the last 10 years:

Options Average Daily Volume (ADV): e.g., 10-day or 30-day trailing options contract volume for the underlying.
25-Delta Risk Reversals (RR25): The implied volatility skew between the 25-delta calls and 25-delta puts.
Volatility Risk Premium (VRP): The spread between Implied Volatility (e.g., 30-day ATM IV) and Realized Volatility.
Put/Call Ratio (PCR): Daily volume and/or open interest Put/Call ratio for the underlying options.

Our Technical Constraint: For computational efficiency and to respect API limits, we absolutely must pull these as pre-calculated, top-level metrics mapped directly to the underlying equity RIC. We cannot build a pipeline that requires us to historically query the entire option chain (strike by strike, expiry by expiry) across 1,000+ stocks every single day for 10 years just to calculate a 25-delta risk reversal or a put/call ratio.

My Questions:

Are there direct TR.* fields available for these specific options metrics that we can pass into rd.get_history()?
If not, does the Instrument Pricing Analytics (IPA) service have a lightweight method to output these specific Greeks and volume metrics historically without querying the full chain?
Are there any specific Data Item Browser formulas or backend data models we should be subscribing to in order to access this point-in-time data cleanly?

Thank you so much in advance for your time and guidance!

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Jirapongse

@Xovizo

Thank you for reaching out to us.

This forum is dedicated to software developers using LSEG APIs. The moderators on this forum do not have deep expertise in every bit of content available through LSEG products, which is required to answer content questions such as this one.

The best resource for content questions is the Helpdesk support team, which can be reached by submitting queries through LSEG Support. The support team will either have the required content expertise ready available or can reach out to relevant content experts to get the answer for you.

You need to ask for the Excel formula, such as =RDP.Data, that can be used to retrieve the required data. Then, we can help you converting that formula to Python code. You can also refer to the How to Convert the =@RDP.Data Excel Function into Code Using the LSEG Data Library for Python article.

For IPA, please refer to the following documents or contact the Instrument Pricing Analytics - Delivery Platform support team directly via LSEG Support.

Please include the URL of this discussion in your raised question to prevent it from being redirected back to this Q&A forum.

beebijankammar_1

=@RDP.Data("VOD.L;CL880G26","TR.AvgDailyVolume10Day;TR.AvgDailyVolume30D;TR.60DAYATTHEMONEYIMPLIEDVOLATILITYINDEXFORCALLOPTIONS;TR.30DAYATTHEMONEYIMPLIEDVOLATILITYINDEXFORPUTOPTIONS;TR.WACCERP","CH=Fd RH=IN",B2)

Jirapongse

@beebijankammar_1

The code looks like this:

ld.get_data(
    universe = ['VOD.L','CL880G26'],
    fields  = ['TR.AvgDailyVolume10Day',
               'TR.AvgDailyVolume30D',
               'TR.60DAYATTHEMONEYIMPLIEDVOLATILITYINDEXFORCALLOPTIONS',
               'TR.30DAYATTHEMONEYIMPLIEDVOLATILITYINDEXFORPUTOPTIONS',
               'TR.WACCERP'])

Please confirm that it is the data required by the client.

This is the output from the code.

Xovizo

Hi @Jirapongse !

Thank you for your answer. I have initially contacted LSEG Support like I always do when I have questions relating to Python or Excel formulas, and within the first answer I was told to create an account here and post a question directly on this community and was told "All API and Python users are encouraged to register on this portal and post their queries there. These will be addressed directly by the LSEG Developers on priority."

Anyway, thank you for your response, I will look into your leads.

Xovizo

Thank you, am actively having a look at this and translating directly into Python.

Jirapongse

@Xovizo

We need to distinguish between content-related questions and technical questions. This forum is intended for technical discussions only.

For content-related questions like this one, the content team should first confirm whether the requested data is available in the database or source system. When reaching out to the content team, it is best to request the specific Workspace Excel formula used to retrieve the data.

Typically, data retrieved via both Excel and Python originates from the same endpoint or source. Therefore, if the data can be accessed through Workspace Excel, it is likely that the same data can also be retrieved using Python code.

We should ask the helpdesk team to verify which fields and parameters are available in Workspace Excel for retrieving the required data. Once this is confirmed, we can easily translate the logic into Python code.

Xovizo

No problem, I will do that. Besides, thank you so much for the documentation they provided, because I really found a way to get historical risk reversals and implied volatility ratios. All that's left for me is to find:

the average daily volume over 10 days or 30 days for the options market of a particular stock
the put to call ratio of a particular stock

It was never my intent to come here and nag you guys. I was told to do this by the support team because they said that what I was requesting is possible, but they were not qualified to answer.

Should I contact them directly, mentioning your answers and our real conversation, so that you don't have to be bothered again?

Jirapongse

@Xovizo

I found that we can retrieve all option RICs for AAPL.O from this chain RIC (0#AAPL*.U). After getting the option RICs, we can use the get_data method to retrieve data or get_history method to retrieve historical data.

from lseg.data.discovery import Chain
chain = Chain("0#AAPL*.U")
print(len(chain.constituents))
ld.get_data(
    universe = chain.constituents[0:10],
    fields = ['EXPIR_DATE','STRIKE_PRC','PUTCALLIND'])

There are 3598 option RICs for AAPL.O.

beebijankammar_1

Most traded Options stats.xlsx

here are the formula

Xovizo

Brilliant, thank you so much Beebijan, this totally solves everything.

Thank you both once again @Jirapongse @beebijankammar_1

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