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Statistical modeling of SOFR term structure

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  • Teemu Pennanen
  • Waleed Taoum

Abstract

SOFR derivatives market remains illiquid and incomplete so it is not amenable to classical risk-neutral term structure models which are based on the assumption of perfect liquidity and completeness. This paper develops a statistical SOFR term structure model that is well-suited for risk management and derivatives pricing within the incomplete markets paradigm. The model incorporates relevant macroeconomic factors that drive central bank policy rates which, in turn, cause jumps often observed in the SOFR rates. The model is easy to calibrate to historical data, current market quotes, and the user's views concerning the future development of the relevant macroeconomic factors. The model is well suited for large-scale simulations often required in risk management, portfolio optimization and indifference pricing of interest rate derivatives.

Suggested Citation

  • Teemu Pennanen & Waleed Taoum, 2025. "Statistical modeling of SOFR term structure," Papers 2508.02691, arXiv.org, revised Nov 2025.
    • Handle: RePEc:arx:papers:2508.02691
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    References listed on IDEAS

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    1. Yu, Wei-Choun & Zivot, Eric, 2011. "Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 579-591.
    2. Erik Schlã–Gl & Jacob Bjerre Skov & David Skovmand, 2024. "Term Structure Modeling Of Sofr: Evaluating The Importance Of Scheduled Jumps," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 27(02), pages 1-34, March.
    3. Teemu Pennanen, 2014. "Optimal investment and contingent claim valuation in illiquid markets," Finance and Stochastics, Springer, vol. 18(4), pages 733-754, October.
    4. Jacob Bjerre Skov & David Skovmand, 2021. "Dynamic Term Structure Models for SOFR Futures," Papers 2103.11180, arXiv.org.
    5. Jacob Bjerre Skov & David Skovmand, 2021. "Dynamic term structure models for SOFR futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1520-1544, October.
    6. Sergio Alvares Maffra & John Armstrong & Teemu Pennanen, 2021. "Stochastic modeling of assets and liabilities with mortality risk," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2021(8), pages 695-725, September.
    7. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
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