The LSEG Data Library for Python offers user-friendly interfaces that provide developers with consistent access to the extensive financial data and services available on the LSEG Data Platform. The API is designed to deliver uniform access across multiple channels, catering to both professional developers and financial coders. Users can retrieve content from their desktop environment, via deployed streaming services, or directly through cloud-based solutions.
In this article I would like to cover one of these content types - the Volatility Surface offering - in more detail.
Volatility Surfaces, like other pricing data (ZC Curves, Inflation Curves), are used to model risk factors and can be used to power risk management or valuation systems. The Volatility Surface can also be analysed across Tenors or Strikes (as per the examples below) to get a sense of how the risk is distributed along these axis.
I think the best way to highlight this content is via some code and some colourful graphs - so let me dive straight into the code....
For the full article, please refer to the Instrument Pricing Analytics - Volatility Surfaces and Curves article on the LSEG Devloper Community.