IDEAS home Printed from https://ideas.repec.org/a/wly/japmet/v31y2016i2p338-356.html
   My bibliography  Save this article

An Empirical Test of Pricing Kernel Monotonicity

Author

Listed:
  • Brendan K. Beare
  • Lawrence D. W. Schmidt

Abstract

A recent literature in finance concerns a curious recurring feature of estimated pricing kernels. Classical theory dictates that the pricing kernel { defined loosely as the ratio of Arrow security prices to an objective probability measure { should be a decreasing function of aggregate resources. Yet a large number of recent empirical studies appear to contradict this prediction. The nonmonotonicity of empirical pricing kernel estimates has become known as the pricing kernel puzzle. In this paper we propose and apply a formal statistical test of pricing kernel monotonicity. The test involves assessing the concavity of the ordinal dominance curve associated with the risk neutral and physical return distributions. We apply the test using thirteen years of data from the market for European put and call options written on the S&P 500 index. Statistically significant violations of pricing kernel monotonicity occur in a substantial proportion of months.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Brendan K. Beare & Lawrence D. W. Schmidt, 2016. "An Empirical Test of Pricing Kernel Monotonicity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 338-356, March.
  • Handle: RePEc:wly:japmet:v:31:y:2016:i:2:p:338-356
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. Dybvig, Philip H, 1988. "Distributional Analysis of Portfolio Choice," The Journal of Business, University of Chicago Press, vol. 61(3), pages 369-393, July.
    3. Fousseni Chabi-Yo & René Garcia & Eric Renault, 2008. "State Dependence Can Explain the Risk Aversion Puzzle," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 973-1011, April.
    4. Giovanni BARONE-ADESI & Hakim DALL'O, 2010. "Is the Price Kernel Monotone?," Swiss Finance Institute Research Paper Series 10-03, Swiss Finance Institute, revised Apr 2010.
    5. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    6. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    7. Alexandre Ziegler, 2007. "Why Does Implied Risk Aversion Smile?," Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 859-904.
    8. Wolfgang Karl Härdle & Yarema Okhrin & Weining Wang, 2015. "Uniform Confidence Bands for Pricing Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 376-413.
    9. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    10. George M. Constantinides & Jens Carsten Jackwerth & Stylianos Perrakis, 2009. "Mispricing of S&P 500 Index Options," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1247-1277.
    11. Patton, Andrew J. & Timmermann, Allan, 2010. "Monotonicity in asset returns: New tests with applications to the term structure, the CAPM, and portfolio sorts," Journal of Financial Economics, Elsevier, vol. 98(3), pages 605-625, December.
    12. Jackwerth, Jens Carsten, 2000. "Recovering Risk Aversion from Option Prices and Realized Returns," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 433-451.
    13. Bakshi, Gurdip & Madan, Dilip & Panayotov, George, 2010. "Returns of claims on the upside and the viability of U-shaped pricing kernels," Journal of Financial Economics, Elsevier, vol. 97(1), pages 130-154, July.
    14. Yuri Golubev & Wolfgang Härdle & Roman Timonfeev, 2008. "Testing Monotonicity of Pricing Kernels," SFB 649 Discussion Papers SFB649DP2008-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, "undated". "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, Department of Economics and Business Economics, Aarhus University.
    16. 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.
    17. Christopher A. Carolan & Joshua M. Tebbs, 2005. "Nonparametric tests for and against likelihood ratio ordering in the two-sample problem," Biometrika, Biometrika Trust, vol. 92(1), pages 159-171, March.
    18. Wolfgang Härdle & Volker Krätschmer & Rouslan Moro, 2009. "A Microeconomic Explanation of the EPK Paradox," SFB 649 Discussion Papers SFB649DP2009-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Kai Detlefsen & Wolfgang Härdle & Rouslan Moro, 2007. "Empirical Pricing Kernels and Investor Preferences," SFB 649 Discussion Papers SFB649DP2007-017, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    20. Thorsten HENS & Christian REICHLIN, 2010. "Three Solutions to the Pricing Kernel Puzzle," Swiss Finance Institute Research Paper Series 10-14, Swiss Finance Institute.
    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. Denis Belomestny & Wolfgang Karl Härdle & Ekaterina Krymova, 2017. "Sieve Estimation Of The Minimal Entropy Martingale Marginal Density With Application To Pricing Kernel Estimation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(06), pages 1-21, September.
    2. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    3. George M. Constantinides & Michal Czerwonko & Stylianos Perrakis, 2020. "Mispriced index option portfolios," Financial Management, Financial Management Association International, vol. 49(2), pages 297-330, June.
    4. Brendan K. Beare & Juwon Seo, 2022. "Stochastic arbitrage with market index options," Papers 2207.00949, arXiv.org, revised Jul 2022.
    5. Amine Ouazad, 2022. "Do Investors Hedge Against Green Swans? Option-Implied Risk Aversion to Wildfires," Papers 2208.06930, arXiv.org.
    6. Tjeerd de Vries, 2021. "A Tale of Two Tails: A Model-free Approach to Estimating Disaster Risk Premia and Testing Asset Pricing Models," Papers 2105.08208, arXiv.org, revised Oct 2023.
    7. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
    8. Victor Chernozhukov & Whitney K. Newey & Andres Santos, 2023. "Constrained Conditional Moment Restriction Models," Econometrica, Econometric Society, vol. 91(2), pages 709-736, March.
    9. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Oct 2022.
    10. Beare, Brendan K. & Shi, Xiaoxia, 2019. "An improved bootstrap test of density ratio ordering," Econometrics and Statistics, Elsevier, vol. 10(C), pages 9-26.
    11. Zheng Fang, 2021. "A Unifying Framework for Testing Shape Restrictions," Papers 2107.12494, arXiv.org, revised Aug 2021.
    12. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    13. Marinelli, Carlo & d’Addona, Stefano, 2017. "Nonparametric estimates of pricing functionals," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 19-35.
    14. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
    15. Xi Chen & Victor Chernozhukov & Iv'an Fern'andez-Val & Scott Kostyshak & Ye Luo, 2018. "Shape-Enforcing Operators for Point and Interval Estimators," Papers 1809.01038, arXiv.org, revised Feb 2021.
    16. Jiao, Yuhan & Liu, Qiang & Guo, Shuxin, 2021. "Pricing kernel monotonicity and term structure: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 123(C).
    17. Ricardo Crisóstomo, 2021. "Estimación de probabilidades representativas del mundo real: importancia de los sesgos conductuales," CNMV Documentos de Trabajo CNMV Documentos de Trabaj, CNMV- Comisión Nacional del Mercado de Valores - Departamento de Estudios y Estadísticas.
    18. Mr. Ralph Chami & Mr. Thomas F. Cosimano & Ms. Celine Rochon & Julieta Yung, 2020. "Riding the Yield Curve: Risk Taking Behavior in a Low Interest Rate Environment," IMF Working Papers 2020/053, International Monetary Fund.
    19. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    20. Denis Belomestny & Shujie Ma & Wolfgang Karl Härdle, 2015. "Pricing Kernel Modeling," SFB 649 Discussion Papers SFB649DP2015-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.
    22. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. Xinyu WU & Senchun REN & Hailin ZHOU, 2017. "Empirical Pricing Kernels: Evidence from the Hong Kong Stock Market," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 263-278.
    24. Seo, Juwon, 2018. "Tests of stochastic monotonicity with improved power," Journal of Econometrics, Elsevier, vol. 207(1), pages 53-70.

    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. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    2. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    3. Stylianos Perrakis, 2022. "From innovation to obfuscation: continuous time finance fifty years later," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(3), pages 369-401, September.
    4. Maria Grith & Wolfgang Karl Härdle & Volker Krätschmer, 2013. "Reference Dependent Preferences and the EPK Puzzle," SFB 649 Discussion Papers SFB649DP2013-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    5. Brendan K. Beare, 2023. "Optimal measure preserving derivatives revisited," Mathematical Finance, Wiley Blackwell, vol. 33(2), pages 370-388, April.
    6. Brendan K. Beare & Juwon Seo, 2022. "Stochastic arbitrage with market index options," Papers 2207.00949, arXiv.org, revised Jul 2022.
    7. David Backus & Mikhail Chernov & Ian Martin, 2011. "Disasters Implied by Equity Index Options," Journal of Finance, American Finance Association, vol. 66(6), pages 1969-2012, December.
    8. Bakshi, Gurdip & Madan, Dilip & Panayotov, George, 2010. "Returns of claims on the upside and the viability of U-shaped pricing kernels," Journal of Financial Economics, Elsevier, vol. 97(1), pages 130-154, July.
    9. Polkovnichenko, Valery & Zhao, Feng, 2013. "Probability weighting functions implied in options prices," Journal of Financial Economics, Elsevier, vol. 107(3), pages 580-609.
    10. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle in forward looking data," Review of Derivatives Research, Springer, vol. 21(3), pages 253-276, October.
    11. Xinyu WU & Senchun REN & Hailin ZHOU, 2017. "Empirical Pricing Kernels: Evidence from the Hong Kong Stock Market," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 263-278.
    12. Wolfgang Härdle & Volker Krätschmer & Rouslan Moro, 2009. "A Microeconomic Explanation of the EPK Paradox," SFB 649 Discussion Papers SFB649DP2009-010, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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. George M. Constantinides & Michal Czerwonko & Stylianos Perrakis, 2020. "Mispriced index option portfolios," Financial Management, Financial Management Association International, vol. 49(2), pages 297-330, June.
    15. Audrino, Francesco & Meier, Pirmin, 2012. "Empirical pricing kernel estimation using a functional gradient descent algorithm based on splines," Economics Working Paper Series 1210, University of St. Gallen, School of Economics and Political Science.
    16. Yuri Golubev & Wolfgang Härdle & Roman Timofeev, 2014. "Testing monotonicity of pricing kernels," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(4), pages 305-326, October.
    17. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    18. Barone-Adesi, Giovanni & Fusari, Nicola & Mira, Antonietta & Sala, Carlo, 2020. "Option market trading activity and the estimation of the pricing kernel: A Bayesian approach," Journal of Econometrics, Elsevier, vol. 216(2), pages 430-449.
    19. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
    20. 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.

    More about this item

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. An Empirical Test of Pricing Kernel Monotonicity (Journal of Applied Econometrics 2016) in ReplicationWiki

    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:wly:japmet:v:31:y:2016:i:2:p:338-356. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0883-7252/ .

    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.