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Estimating option implied risk-neutral densities using spline and hypergeometric functions

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  • Ruijun Bu
  • Kaddour Hadri

Abstract

We examine the ability of two recent methods -- the smoothed implied volatility smile method (SML) and the density functionals based on confluent hypergeometric functions (DFCH) -- for estimating implied risk-neutral densities (RNDs) from European-style options. Two complementary Monte Carlo experiments are conducted and the performance of the two RND estimators is evaluated by the root mean integrated squared error (RMISE) criterion. Results from both experiments show that the DFCH method outperforms the SML method for the overall quality of the estimated RNDs concerning both accuracy and stability. An application of the two methods to the OTC currency options market is also presented. Copyright Royal Economic Society 2007

Suggested Citation

  • Ruijun Bu & Kaddour Hadri, 2007. "Estimating option implied risk-neutral densities using spline and hypergeometric functions," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 216-244, July.
    • Handle: RePEc:ect:emjrnl:v:10:y:2007:i:2:p:216-244
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    Cited by:

    1. van Wijnbergen, Sweder & Olijslagers, Stan & Petersen, Annelie & de Vette, Nander, 2018. "What Option Prices tell us about the ECB's Unconventional Monetary Policies," CEPR Discussion Papers 13371, C.E.P.R. Discussion Papers.
    2. Alexander Veremyev & Peter Tsyurmasto & Stan Uryasev & R. Rockafellar, 2014. "Calibrating probability distributions with convex-concave-convex functions: application to CDO pricing," Computational Management Science, Springer, vol. 11(4), pages 341-364, October.
    3. Ruijun Bu & Fredj Jawadi & Yuyi Li, 2020. "A multifactor transformed diffusion model with applications to VIX and VIX futures," Econometric Reviews, Taylor & Francis Journals, vol. 39(1), pages 27-53, January.
    4. 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.
    5. Seung Hwan Lee, 2014. "Estimation of risk-neutral measures using quartic B-spline cumulative distribution functions with power tails," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1857-1879, October.
    6. Xixuan Han & Boyu Wei & Hailiang Yang, 2018. "Index Options And Volatility Derivatives In A Gaussian Random Field Risk-Neutral Density Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-41, June.
    7. Guillermo Benavides Perales & Israel Felipe Mora Cuevas, 2008. "Parametric vs. non-parametric methods for estimating option implied risk-neutral densities: the case of the exchange rate Mexican peso – US dollar," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 33-52, May.
    8. Allan M. Malz, 2014. "Simple and reliable way to compute option-based risk-neutral distributions," Staff Reports 677, Federal Reserve Bank of New York.
    9. Bu, Ruijun & Cheng, Jie & Hadri, Kaddour, 2016. "Reducible diffusions with time-varying transformations with application to short-term interest rates," Economic Modelling, Elsevier, vol. 52(PA), pages 266-277.
    10. Datta, Deepa Dhume & Londono, Juan M. & Ross, Landon J., 2017. "Generating options-implied probability densities to understand oil market events," Energy Economics, Elsevier, vol. 64(C), pages 440-457.
    11. Shan Lu, 2019. "Monte Carlo analysis of methods for extracting risk‐neutral densities with affine jump diffusions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(12), pages 1587-1612, December.
    12. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modeling Multivariate Interest Rates using Time-Varying Copulas and Reducible Stochastic Differential Equations," Working Papers halshs-00408014, HAL.
    13. Chen, Shu-Hsiu, 2017. "Carry trade strategies based on option-implied information: Evidence from a cross-section of funding currencies," Journal of International Money and Finance, Elsevier, vol. 78(C), pages 1-20.
    14. de Vette, Nander & Petersen, Annelie & Stan Olijslager, Stan & van Wijnbergen, Sweder, 2018. "What Option Prices tell us about the ECB's Unconventional Monetary Policies," CEPR Discussion Papers 13371, C.E.P.R. Discussion Papers.
    15. Hardeep Singh Mundi, 2023. "Risk neutral variances to compute expected returns using data from S&P BSE 100 firms—a replication study," Management Review Quarterly, Springer, vol. 73(1), pages 215-230, February.
    16. Jean-Baptiste Monnier, 2013. "Technical report : Risk-neutral density recovery via spectral analysis," Papers 1302.2567, arXiv.org.
    17. Ana M. Monteiro & António A. F. Santos, 2022. "Option prices for risk‐neutral density estimation using nonparametric methods through big data and large‐scale problems," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 152-171, January.
    18. Taboga, Marco, 2016. "Option-implied probability distributions: How reliable? How jagged?," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 453-469.
    19. Arindam Kundu & Sumit Kumar & Nutan Kumar Tomar, 2019. "Option Implied Risk-Neutral Density Estimation: A Robust and Flexible Method," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 705-728, August.
    20. Ruijun Bu & Ludovic Giet & Kaddour Hadri & Michel Lubrano, 2009. "Modelling Multivariate Interest Rates using Time-Varying Copulas and Reducible Non-Linear Stochastic Differential," Economics Working Papers 09-02, Queen's Management School, Queen's University Belfast.
    21. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.

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