Using Numerix & Python to Construct Alternative Reference Rate Curves

Learn the key components for building SOFR curves and performing various types of curve analysis using Numerix CrossAsset’s multi-curve framework and Jupyter Notebooks with Python.

The transition from LIBOR to Alternative Reference Rates (ARRs) seems to be gaining momentum in 2019, especially as liquidity starts to develop in ARR products in some jurisdictions. As LIBOR transition teams continue to strategize and plan their path to using ARRs, many are evaluating their technology capabilities to determine how ARR curves can be implemented in their mission critical systems.

Unfortunately, many legacy systems cannot currently handle ARR curves and firms are trying to determine how to address this problem. If your firm needs help with ARR curve technology, Numerix may be able to help, as Numerix has a robust multi-curve framework with full coverage for ARR curves.

In this webinar, Liang Wu demonstrated how to build SOFR curves using the Numerix CrossAsset Python SDK, walking through the process in a Jupyter Notebook using Python. Jupyter Notebooks are particularly useful for technical demonstrations like this as they are very dynamic, easy-to-understand, and visually engaging.

In addition to covering the basics of ARR curve construction, Mr. Wu walked through some practical curve applications, including an assessment of the P&L impact of moving from a Fed Funds OIS curve to a SOFR curve for LIBOR swaps of different maturities and moneyness. This is literally the million-dollar question for many firms – how will the ARR transition affect my P&L?


  • Curve construction in the multi-curve environment
    • Static data
    • Curve members
    • Curve features
  • Applications with Alternative Reference Rates
    • Newly introduced instruments
    • Curve visualization
    • Par-pricing check
    • Indicative breakeven rates
    • P&L impact analysis
  • Key takeaways

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