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What drives jumps in the secured Overnight Financing Rate? Evidence from the arbitrage-free Nelson–Siegel model with jump diffusion

Author

Listed:
  • Fang, Dong-Jie
  • Yeh, Zong-Wei
  • He, Jie-Cao
  • Lin, Shih-Kuei

Abstract

In this paper, the arbitrage-free Nelson–Siegel (NS) model with jump diffusion (AFNSJ) is proposed to describe the Secured Overnight Financing Rate (SOFR). The parameters of this model are estimated through particle filtering conducted with a weighted maximum likelihood estimation approach. The empirical results of this study indicate that the AFNSJ outperforms the arbitrage-free NS model in fitting market data. SOFR jumps are highly related to Federal Open Market Committee meetings. Moreover, even under different interest rate changes, these jumps are mainly driven by a short-term factor. The risk adjustment term can suitably capture changes in the US Federal Reserve rate caused by the jump risk component.

Suggested Citation

  • Fang, Dong-Jie & Yeh, Zong-Wei & He, Jie-Cao & Lin, Shih-Kuei, 2024. "What drives jumps in the secured Overnight Financing Rate? Evidence from the arbitrage-free Nelson–Siegel model with jump diffusion," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:pacfin:v:86:y:2024:i:c:s0927538x24001434
    DOI: 10.1016/j.pacfin.2024.102392
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    References listed on IDEAS

    as
    1. Erik Heitfield & Yang-Ho Park, 2019. "Inferring Term Rates from SOFR Futures Prices," Finance and Economics Discussion Series 2019-014, Board of Governors of the Federal Reserve System (U.S.).
    2. Das, Sanjiv R., 2002. "The surprise element: jumps in interest rates," Journal of Econometrics, Elsevier, vol. 106(1), pages 27-65, January.
    3. Pan, Jun, 2002. "The jump-risk premia implicit in options: evidence from an integrated time-series study," Journal of Financial Economics, Elsevier, vol. 63(1), pages 3-50, January.
    4. Creal, Drew D. & Wu, Jing Cynthia, 2015. "Estimation of affine term structure models with spanned or unspanned stochastic volatility," Journal of Econometrics, Elsevier, vol. 185(1), pages 60-81.
    5. Jacob Bjerre Skov & David Skovmand, 2021. "Dynamic Term Structure Models for SOFR Futures," Papers 2103.11180, arXiv.org.
    6. Pierluigi Balduzzi & Sanjiv Ranjan Das & Silverio Foresi, 1998. "The Central Tendency: A Second Factor In Bond Yields," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 62-72, February.
    7. James D. Hamilton & Jing Cynthia Wu, 2012. "The Effectiveness of Alternative Monetary Policy Tools in a Zero Lower Bound Environment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(s1), pages 3-46, February.
    8. Cheridito, Patrick & Filipovic, Damir & Kimmel, Robert L., 2007. "Market price of risk specifications for affine models: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 83(1), pages 123-170, January.
    9. David Skovmand & Jacob Bjerre Skov, 2022. "Decomposing LIBOR in Transition: Evidence from the Futures Markets," Papers 2201.06930, arXiv.org, revised Mar 2022.
    10. Qiang Dai & Kenneth J. Singleton, 2000. "Specification Analysis of Affine Term Structure Models," Journal of Finance, American Finance Association, vol. 55(5), pages 1943-1978, October.
    11. Gregory R. Duffee, 2002. "Term Premia and Interest Rate Forecasts in Affine Models," Journal of Finance, American Finance Association, vol. 57(1), pages 405-443, February.
    12. Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
    13. Robert Jarrow & Haitao Li & Feng Zhao, 2007. "Interest Rate Caps “Smile” Too! But Can the LIBOR Market Models Capture the Smile?," Journal of Finance, American Finance Association, vol. 62(1), pages 345-382, February.
    14. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 523-543, December.
    15. repec:bla:jfinan:v:59:y:2004:i:1:p:227-260 is not listed on IDEAS
    16. 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.
    17. Claudio Fontana & Zorana Grbac & Thorsten Schmidt, 2022. "Term structure modelling with overnight rates beyond stochastic continuity," Working Papers hal-03898872, HAL.
    18. Jefferson Duarte, 2004. "Evaluating an Alternative Risk Preference in Affine Term Structure Models," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 379-404.
    19. Faust, Jon & Rogers, John H. & Wang, Shing-Yi B. & Wright, Jonathan H., 2007. "The high-frequency response of exchange rates and interest rates to macroeconomic announcements," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1051-1068, May.
    20. Christensen, Jens H.E. & Diebold, Francis X. & Rudebusch, Glenn D., 2011. "The affine arbitrage-free class of Nelson-Siegel term structure models," Journal of Econometrics, Elsevier, vol. 164(1), pages 4-20, September.
    21. Backwell, Alex & Hayes, Joshua, 2022. "Expected and Unexpected Jumps in the Overnight Rate: Consistent Management of the Libor Transition," Journal of Banking & Finance, Elsevier, vol. 145(C).
    22. Kam F. Chan & Philip Gray, 2018. "Volatility jumps and macroeconomic news announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(8), pages 881-897, August.
    23. Karol Gellert & Erik Schlogl, 2021. "Short Rate Dynamics: A Fed Funds and SOFR Perspective," Research Paper Series 420, Quantitative Finance Research Centre, University of Technology, Sydney.
    24. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
    25. repec:bla:jfinan:v:59:y:2004:i:3:p:1201-1234 is not listed on IDEAS
    26. Andrea Macrina & David Skovmand, 2020. "Rational Savings Account Models for Backward-Looking Interest Rate Benchmarks," Risks, MDPI, vol. 8(1), pages 1-18, March.
    27. Guan, Lim Kian & Ting, Christopher & Warachka, Mitch, 2005. "The implied jump risk of LIBOR rates," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2503-2522, October.
    28. Alan Brace & Dariusz G¸atarek & Marek Musiela, 1997. "The Market Model of Interest Rate Dynamics," Mathematical Finance, Wiley Blackwell, vol. 7(2), pages 127-155, April.
    29. 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.
    30. Balduzzi, Pierluigi & Bertola, Giuseppe & Foresi, Silverio, 1997. "A model of target changes and the term structure of interest rates," Journal of Monetary Economics, Elsevier, vol. 39(2), pages 223-249, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Secured Overnight Financing Rate (SOFR); SOFR futures; Arbitrage-free Nelson–Siegel model with jump diffusion (AFNSJ); Federal Open Market Committee (FOMC) meeting; Particle filter;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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