IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v382y2007i1p121-128.html
   My bibliography  Save this article

Non-parametric extraction of implied asset price distributions

Author

Listed:
  • Healy, Jerome V.
  • Dixon, Maurice
  • Read, Brian J.
  • Cai, Fang Fang

Abstract

We present a fully non-parametric method for extracting risk neutral densities (RNDs) from observed option prices. The aim is to obtain a continuous, smooth, monotonic, and convex pricing function that is twice differentiable. Thus, irregularities such as negative probabilities that afflict many existing RND estimation techniques are reduced. Our method employs neural networks to obtain a smoothed pricing function, and a central finite difference approximation to the second derivative to extract the required gradients.

Suggested Citation

  • Healy, Jerome V. & Dixon, Maurice & Read, Brian J. & Cai, Fang Fang, 2007. "Non-parametric extraction of implied asset price distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 121-128.
    • Handle: RePEc:eee:phsmap:v:382:y:2007:i:1:p:121-128
    DOI: 10.1016/j.physa.2007.02.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437107001422
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2007.02.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ait-Sahalia, Yacine & Lo, Andrew W., 2000. "Nonparametric risk management and implied risk aversion," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 9-51.
    2. Dupont, Dominique Y., 2001. "Extracting Risk-Neutral Probability Distributions from Option Prices Using Trading Volume as a Filter," Economics Series 104, Institute for Advanced Studies.
    3. Bhupinder Bahra, 1997. "Implied risk-neutral probability density functions from option prices: theory and application," Bank of England working papers 66, Bank of England.
    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. 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.
    6. Healy, J.V. & Dixon, M. & Read, B.J. & Cai, F.F., 2004. "Confidence limits for data mining models of options prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 162-167.
    7. Neuhaus, Holger, 1995. "The information content of derivatives for monetary policy: Implied volatilities and probabilities," Discussion Paper Series 1: Economic Studies 1995,03e, Deutsche Bundesbank.
    8. Robert J. Ritchey, 1990. "Call Option Valuation For Discrete Normal Mixtures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 13(4), pages 285-296, December.
    9. Panayiotis Andreou & Chris Charalambous & Spiros Martzoukos, 2006. "Robust Artificial Neural Networks for Pricing of European Options," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 329-351, May.
    10. Ritchey, Robert J, 1990. "Call Option Valuation for Discrete Normal Mixtures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 13(4), pages 285-296, Winter.
    11. Garcia, Rene & Gencay, Ramazan, 2000. "Pricing and hedging derivative securities with neural networks and a homogeneity hint," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 93-115.
    12. 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.
    13. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    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. 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. 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.
    3. Johannes Ruf & Weiguan Wang, 2019. "Neural networks for option pricing and hedging: a literature review," Papers 1911.05620, arXiv.org, revised May 2020.

    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. 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.
    3. Bondarenko, Oleg, 2003. "Estimation of risk-neutral densities using positive convolution approximation," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 85-112.
    4. 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.
    5. Wilkens, Sascha & Roder, Klaus, 2006. "The informational content of option-implied distributions: Evidence from the Eurex index and interest rate futures options market," Global Finance Journal, Elsevier, vol. 17(1), pages 50-74, September.
    6. Andersson, Magnus & Lomakka, Magnus, 2005. "Evaluating implied RNDs by some new confidence interval estimation techniques," Journal of Banking & Finance, Elsevier, vol. 29(6), pages 1535-1557, June.
    7. Healy, J.V. & Gregoriou, A. & Hudson, R., 2018. "Test of recent advances in extracting information from option prices," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 292-302.
    8. Liu, Xiaoquan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2007. "Closed-form transformations from risk-neutral to real-world distributions," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1501-1520, May.
    9. Monteiro, Ana Margarida & Tutuncu, Reha H. & Vicente, Luis N., 2008. "Recovering risk-neutral probability density functions from options prices using cubic splines and ensuring nonnegativity," European Journal of Operational Research, Elsevier, vol. 187(2), pages 525-542, June.
    10. Shi-jie Jiang & Mujun Lei & Cheng-Huang Chung, 2018. "An Improvement of Gain-Loss Price Bounds on Options Based on Binomial Tree and Market-Implied Risk-Neutral Distribution," Sustainability, MDPI, vol. 10(6), pages 1-17, June.
    11. Xin Liu, 2016. "Asset Pricing with Random Volatility," Papers 1610.01450, arXiv.org, revised Sep 2018.
    12. Ruijun Bu & Kaddour Hadri, 2005. "Estimating the Risk Neutral Probability Density Functions Natural Spline versus Hypergeometric Approach Using European Style Options," Working Papers 200510, University of Liverpool, Department of Economics.
    13. 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.
    14. Vahamaa, Sami, 2005. "Option-implied asymmetries in bond market expectations around monetary policy actions of the ECB," Journal of Economics and Business, Elsevier, vol. 57(1), pages 23-38.
    15. Martin Mandler, 2002. "Extracting Market Expectations from Option Prices: Two Case Studies in Market Perceptions of the ECB's Monetary Policy 1999/2000," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 138(II), pages 165-189, June.
    16. Liyuan Jiang & Shuang Zhou & Keren Li & Fangfang Wang & Jie Yang, 2018. "A New Nonparametric Estimate of the Risk-Neutral Density with Applications to Variance Swaps," Papers 1808.05289, arXiv.org, revised Feb 2019.
    17. Josep Puigvert-Gutiérrez & Rupert Vincent-Humphreys, 2012. "A Quantitative Mirror on the Euribor Market Using Implied Probability Density Functions," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 2(1), pages 1-31, June.
    18. 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.
    19. Barletta, Andrea & Santucci de Magistris, Paolo & Violante, Francesco, 2019. "A non-structural investigation of VIX risk neutral density," Journal of Banking & Finance, Elsevier, vol. 99(C), pages 1-20.
    20. 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.

    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:eee:phsmap:v:382:y:2007:i:1:p:121-128. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.