IDEAS home Printed from https://ideas.repec.org/p/bde/wpaper/0504.html
   My bibliography  Save this paper

Testing the forecasting performace of IBEX 35 option implied risk neutral densities

Author

Listed:
  • Francisco Alonso

    (Banco de España)

  • Roberto Blanco

    (Banco de España)

  • Gonzalo Rubio

    (Euskal Herriko Unibertsitatea)

Abstract

The main objective of this paper is to test whether the risk neutral densities (RNDs) implied in the prices of the future options contract on the Spanish IBEX 35 index accurately predict the distribution of future outcomes of the underlying asset. We estimate RNDs using both parametric and nonparametric procedures. We find that between 1996 and 2003 we cannot reject the hypothesis that the RNDs provide accurate predictions of the distributions of future realisations of the IBEX 35 index at four week horizon. However, this result is not robust by subperiods. In particular, from October 1996 to February 2000, we find that RNDs are not able to consistently predict the actual realisations of returns. In this period, option prices assign a low risk neutral probability to large rises compared with realisations. Tests based on the tails of the distribution show that RNDs significantly understate the right tail of the distribution for both the whole period and the first subperiod.

Suggested Citation

  • Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2005. "Testing the forecasting performace of IBEX 35 option implied risk neutral densities," Working Papers 0504, Banco de España.
  • Handle: RePEc:bde:wpaper:0504
    as

    Download full text from publisher

    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/05/Fic/dt0504e.pdf
    File Function: First version, February 2005
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-474, October.
    2. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    3. Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
    4. Bondarenko, Oleg, 2003. "Estimation of risk-neutral densities using positive convolution approximation," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 85-112.
    5. Jing-zhi Huang & Liuren Wu, 2004. "Specification Analysis of Option Pricing Models Based on Time-Changed Lévy Processes," Journal of Finance, American Finance Association, vol. 59(3), pages 1405-1440, June.
    6. María C. Manzano & Isabel Sánchez, 1998. "Indicators of Short-Term Interest Rate Expectations. The Information Contained in the Options Market," Working Papers 9816, Banco de España.
    7. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    8. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    9. Melick, William R. & Thomas, Charles P., 1997. "Recovering an Asset's Implied PDF from Option Prices: An Application to Crude Oil during the Gulf Crisis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(1), pages 91-115, March.
    10. Mark Rubinstein., 1994. "Implied Binomial Trees," Research Program in Finance Working Papers RPF-232, University of California at Berkeley.
    11. Yacine Aït-Sahalia & Andrew W. Lo, "undated". "Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices," CRSP working papers 332, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    12. Carr, Peter & Wu, Liuren, 2004. "Time-changed Levy processes and option pricing," Journal of Financial Economics, Elsevier, vol. 71(1), pages 113-141, January.
    13. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    14. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    15. Keller, Joachim & Glatzer, Ernst & Craig, Ben R. & Scheicher, Martin, 2003. "The Forecasting Performance of German Stock Option Densities," Discussion Paper Series 1: Economic Studies 2003,17, Deutsche Bundesbank.
    16. Robert JARROW & Andrew RUDD, 2008. "Approximate Option Valuation For Arbitrary Stochastic Processes," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 1, pages 9-31, World Scientific Publishing Co. Pte. Ltd..
    17. Campa, Jose M. & Chang, P. H. Kevin & Reider, Robert L., 1998. "Implied exchange rate distributions: evidence from OTC option markets1," Journal of International Money and Finance, Elsevier, vol. 17(1), pages 117-160, February.
    18. Bliss, Robert R. & Panigirtzoglou, Nikolaos, 2002. "Testing the stability of implied probability density functions," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 381-422, March.
    19. Steven A. Weinberg, 2001. "Interpreting the volatility smile: an examination of the information content of option prices," International Finance Discussion Papers 706, Board of Governors of the Federal Reserve System (U.S.).
    20. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    21. Rubinstein, Mark, 1994. "Implied Binomial Trees," Journal of Finance, American Finance Association, vol. 49(3), pages 771-818, July.
    22. Yacine Aït-Sahalia & Andrew W. Lo, 1998. "Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices," Journal of Finance, American Finance Association, vol. 53(2), pages 499-547, April.
    23. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ricardo Crisóstomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
    2. Maria Grith & Wolfgang K. Härdle & Volker Krätschmer, 2017. "Reference-Dependent Preferences and the Empirical Pricing Kernel Puzzle," Review of Finance, European Finance Association, vol. 21(1), pages 269-298.
    3. Alonso, Francisco & Blanco, Roberto & Rubio Irigoyen, Gonzalo, 2005. "Option-Implied Preferences Adjustments and Risk-Neutral Density Forecasts," DFAEII Working Papers 1988-088X, University of the Basque Country - Department of Foundations of Economic Analysis II.
    4. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2009. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Spanish Economic Review, Springer;Spanish Economic Association, vol. 11(2), pages 141-164, June.
    5. Duca, Ioana Andreea & Ruxanda, Gheorghe, 2013. "A View on the Risk-Neutral Density Forecasting of the Dax30 Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 101-114, June.
    6. Birru, Justin & Figlewski, Stephen, 2012. "Anatomy of a meltdown: The risk neutral density for the S&P 500 in the fall of 2008," Journal of Financial Markets, Elsevier, vol. 15(2), pages 151-180.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    3. Marian Micu, 2005. "Extracting expectations from currency option prices: a comparison of methods," Computing in Economics and Finance 2005 226, Society for Computational Economics.
    4. 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.
    5. Francisco Alonso & Roberto Blanco & Gonzalo Rubio, 2009. "Option-implied preferences adjustments, density forecasts, and the equity risk premium," Spanish Economic Review, Springer;Spanish Economic Association, vol. 11(2), pages 141-164, June.
    6. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    7. 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.
    8. Christoffersen, Peter & Heston, Steven & Jacobs, Kris, 2010. "Option Anomalies and the Pricing Kernel," Working Papers 11-17, University of Pennsylvania, Wharton School, Weiss Center.
    9. Li, Minqiang, 2008. "Price Deviations of S&P 500 Index Options from the Black-Scholes Formula Follow a Simple Pattern," MPRA Paper 11530, University Library of Munich, Germany.
    10. Jondeau, Eric & Rockinger, Michael, 2000. "Reading the smile: the message conveyed by methods which infer risk neutral densities," Journal of International Money and Finance, Elsevier, vol. 19(6), pages 885-915, December.
    11. Duca, Ioana Andreea & Ruxanda, Gheorghe, 2013. "A View on the Risk-Neutral Density Forecasting of the Dax30 Returns," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 101-114, June.
    12. Bondarenko, Oleg, 2003. "Estimation of risk-neutral densities using positive convolution approximation," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 85-112.
    13. Jondeau, E. & Rockinger, M., 1998. "Reading the Smile: The Message Conveyed by Methods Which Infer Risk Neutral," Working papers 47, Banque de France.
    14. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    15. René Garcia & Eric Ghysels & Eric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
    16. Jin Zhang & Yi Xiang, 2008. "The implied volatility smirk," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 263-284.
    17. Rihab Bedoui & Haykel Hamdi, 2010. "Implied Risk-Neutral probability Density functions from options prices: A comparison of estimation methods," Working Papers hal-04140913, HAL.
    18. Fabozzi, Frank J. & Leccadito, Arturo & Tunaru, Radu S., 2014. "Extracting market information from equity options with exponential Lévy processes," Journal of Economic Dynamics and Control, Elsevier, vol. 38(C), pages 125-141.
    19. Bogdan Negrea & Bertrand Maillet & Emmanuel Jurczenko, 2002. "Revisited Multi-moment Approximate Option," FMG Discussion Papers dp430, Financial Markets Group.
    20. Liu, Xiaoquan & Cao, Yi & Ma, Chenghu & Shen, Liya, 2019. "Wavelet-based option pricing: An empirical study," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1132-1142.

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bde:wpaper:0504. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ángel Rodríguez. Electronic Dissemination of Information Unit. Research Department. Banco de España (email available below). General contact details of provider: https://edirc.repec.org/data/bdegves.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.