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Nonparametric Estimation of State-Price Densities Implicit in Interest Rate Cap Prices

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  • Haitao Li
  • Feng Zhao

Abstract

Based on a multivariate extension of the constrained locally polynomial estimator of Aït-Sahalia and Duarte (2003), we provide one of the first nonparametric estimates of probability densities of LIBOR rates under forward martingale measures and state-price densities (SPDs) implicit in interest rate cap prices. The forward densities and SPDs depend significantly on the slope and volatility of LIBOR rates, and mortgage markets activities have strong impacts on the shape of the forward densities. The SPDs exhibit a pronounced U-shape as a function of future LIBOR rates, suggesting that the state prices are high at both extremely low and high interest rates, which tend to be associated with recessions and periods of high inflation, respectively. Our results provide nonparametric evidence of unspanned stochastic volatility and suggest that the unspanned factors could be partly driven by activities in the mortgage markets. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

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  • Haitao Li & Feng Zhao, 2009. "Nonparametric Estimation of State-Price Densities Implicit in Interest Rate Cap Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4335-4376, November.
    • Handle: RePEc:oup:rfinst:v:22:y:2009:i:11:p:4335-4376
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    2. Ivanova, Vesela & Puigvert Gutiérrez, Josep Maria, 2014. "Interest rate forecasts, state price densities and risk premium from Euribor options," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 210-223.
    3. Backwell, Alex, 2021. "Unspanned stochastic volatility from an empirical and practical perspective," Journal of Banking & Finance, Elsevier, vol. 122(C).
    4. Kitsul, Yuriy & Wright, Jonathan H., 2013. "The economics of options-implied inflation probability density functions," Journal of Financial Economics, Elsevier, vol. 110(3), pages 696-711.
    5. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    6. Leippold, Markus & Strømberg, Jacob, 2014. "Time-changed Lévy LIBOR market model: Pricing and joint estimation of the cap surface and swaption cube," Journal of Financial Economics, Elsevier, vol. 111(1), pages 224-250.
    7. Coenen, Günter & Montes-Galdón, Carlos & Saint Guilhem, Arthur & Hutchinson, John & Motto, Roberto, 2022. "Rate forward guidance in an environment of large central bank balance sheets: a Eurosystem stock-taking assessment," Occasional Paper Series 290, European Central Bank.
    8. J. Arismendi-Zambrano & R. Azevedo, 2020. "Implicit Entropic Market Risk-Premium from Interest Rate Derivatives," Economics Department Working Paper Series n303-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    9. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    10. Covarrubias, Enrique & Hernández-del-Valle, Gerardo, 2016. "Inflation expectations derived from a portfolio model," MPRA Paper 69489, University Library of Munich, Germany.
    11. Biao Guo & Qian Han & Doojin Ryu, 2013. "The Number of State Variables for CDS Pricing," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    12. Karl Härdle, Wolfgang & López-Cabrera, Brenda & Teng, Huei-Wen, 2015. "State price densities implied from weather derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 106-125.
    13. Song, Zhaogang & Xiu, Dacheng, 2016. "A tale of two option markets: Pricing kernels and volatility risk," Journal of Econometrics, Elsevier, vol. 190(1), pages 176-196.
    14. Frédéric Vrins & Linqi Wang, 2023. "Asymmetric short-rate model without lower bound," Quantitative Finance, Taylor & Francis Journals, vol. 23(2), pages 279-295, February.
    15. Kwai S. Leung & Hon Y. Ng & Hoi Y. Wong, 2014. "Stochastic Skew in the Interest Rate Cap Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(12), pages 1146-1169, December.
    16. Fousseni Chabi-Yo, 2012. "Pricing Kernels with Stochastic Skewness and Volatility Risk," Management Science, INFORMS, vol. 58(3), pages 624-640, March.
    17. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    18. Lu, Junwen & Qu, Zhongjun, 2021. "Sieve estimation of option-implied state price density," Journal of Econometrics, Elsevier, vol. 224(1), pages 88-112.
    19. Meng, Bo & Vijh, Anand M., 2021. "Stock merger activity and industry performance," Journal of Banking & Finance, Elsevier, vol. 129(C).
    20. Gang Li & Chu Zhang, 2010. "On the Number of State Variables in Options Pricing," Management Science, INFORMS, vol. 56(11), pages 2058-2075, November.
    21. Li, Gang & Zhang, Chu, 2013. "Diagnosing affine models of options pricing: Evidence from VIX," Journal of Financial Economics, Elsevier, vol. 107(1), pages 199-219.

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