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Quadratic term structure models in discrete time

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Abstract

This paper extends the results on quadratic term structure models in continuos time to the discrete time setting. The continuos time setting can be seen as a special case of the discrete time one. Recursive closed form solutions for zero coupon bonds are provided even in the presence of multiple correlated underlying factors. Pricing bond options requires simple integration. Model parameters may well be time dependent without scuppering such tractability. Model estimation does not require a restrictive choice of the market price of risk. The model can also be used for pricing credit risk and is particularly useful when the factors are or depend on periodically released macroeconomic data or corporate financial reports.
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  • Realdon, Marco, 2006. "Quadratic term structure models in discrete time," Finance Research Letters, Elsevier, vol. 3(4), pages 277-289, December.
    • Handle: RePEc:eee:finlet:v:3:y:2006:i:4:p:277-289
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    Cited by:

    1. Andreasen, Martin M & Meldrum, Andrew, 2015. "Dynamic term structure models: the best way to enforce the zero lower bound in the United States," Bank of England working papers 550, Bank of England.
    2. Marcello Pericoli & Marco Taboga, 2022. "Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(5), pages 807-838.
    3. Chung, Tsz-Kin & Hui, Cho-Hoi & Li, Ka-Fai, 2017. "Term-structure modelling at the zero lower bound: Implications for estimating the forward term premium," Finance Research Letters, Elsevier, vol. 21(C), pages 100-106.
    4. Anne Lundgaard Hansen, 2018. "Volatility-Induced Stationarity and Error-Correction in Macro-Finance Term Structure Modeling," Discussion Papers 18-12, University of Copenhagen. Department of Economics.
    5. Hansen, Anne Lundgaard, 2021. "Modeling persistent interest rates with double-autoregressive processes," Journal of Banking & Finance, Elsevier, vol. 133(C).
    6. Andreasen, Martin M. & Christensen, Bent Jesper, 2015. "The SR approach: A new estimation procedure for non-linear and non-Gaussian dynamic term structure models," Journal of Econometrics, Elsevier, vol. 184(2), pages 420-451.
    7. Martin M. Andreasen & Andrew C. Meldrum, 2018. "A Shadow Rate or a Quadratic Policy Rule? The Best Way to Enforce the Zero Lower Bound in the United States," Finance and Economics Discussion Series 2018-056, Board of Governors of the Federal Reserve System (U.S.).
    8. Marco Realdon, 2006. "Equity Valuation Under Stochastic Interest Rates," Discussion Papers 06/12, Department of Economics, University of York.
    9. Bruno Feunou & Jean-Sébastien Fontaine & Anh Le & Christian Lundblad, 2022. "Tractable Term Structure Models," Management Science, INFORMS, vol. 68(11), pages 8411-8429, November.
    10. Andreasen, Martin & Meldrum, Andrew, 2013. "Likelihood inference in non-linear term structure models: the importance of the lower bound," Bank of England working papers 481, Bank of England.
    11. Campbell, John Y. & Sunderam, Adi & Viceira, Luis M., 2017. "Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds," Critical Finance Review, now publishers, vol. 6(2), pages 263-301, September.
    12. Realdon, Marco, 2016. "Tests of non linear Gaussian term structure models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 128-147.

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    More about this item

    JEL classification:

    • 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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