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Uniform Confidence Bands for Pricing Kernels

Author

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  • Wolfgang Karl Härdle
  • Yarema Okhrin
  • Weining Wang

Abstract

Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (PK) given by the ratio of the risk-neutral density estimator and the historical density (HD). The former density can be represented as the second derivative w.r.t. the European call option price function, which we estimate by nonparametric regression. HD is estimated nonparametrically too. In this framework, we develop the asymptotic distribution theory of the Empirical Pricing Kernel (EPK) in the L∞ sense. Particularly, to evaluate the overall variation of the pricing kernel, we develop a uniform confidence band of the EPK. Furthermore, as an alternative to the asymptotic approach, we propose a bootstrap confidence band. The developed theory is helpful for testing parametric specifications of pricing kernels and has a direct extension to estimating risk aversion patterns. The established results are assessed and compared in a Monte-Carlo study. As a real application, we test risk aversion over time induced by the EPK.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:jfinec:v:13:y:2015:i:2:p:376-413.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbu002
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    1. Nicole Wiebach & Lutz Hildebrandt, 2010. "Context Effects as Customer Reaction on Delisting of Brands," SFB 649 Discussion Papers SFB649DP2010-056, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Agnieszka Janek & Tino Kluge & Rafal Weron & Uwe Wystup, 2010. "FX Smile in the Heston Model," HSC Research Reports HSC/10/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    3. 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.
    4. 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.
    5. Nikolaus Hautsch & Peter Malec & Melanie Schienle, 2014. "Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 89-121.
    6. Wolfgang Karl Härdle & Rouslan Moro & Linda Hoffmann, 2010. "Learning Machines Supporting Bankruptcy Prediction," SFB 649 Discussion Papers SFB649DP2010-032, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Basteck, Christian & Daniëls, Tijmen R., 2011. "Every symmetric 3×3 global game of strategic complementarities has noise-independent selection," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 749-754.
    8. Franziska Schulze, 2010. "Spatial Dependencies in German Matching Functions," SFB 649 Discussion Papers SFB649DP2010-054, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    9. Krzysztof Burnecki & Joanna Janczura & Rafal Weron, 2010. "Building Loss Models," HSC Research Reports HSC/10/03, Hugo Steinhaus Center, Wroclaw University of Technology.
    10. Alexander L. Baranovski, 2010. "Dynamical systems forced by shot noise as a new paradigm in the interest rate modeling," SFB 649 Discussion Papers SFB649DP2010-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    11. Ulrich Horst & Santiago Moreno-Bromberg, 2010. "Efficiency and Equilibria in Games of Optimal Derivative Design," SFB 649 Discussion Papers SFB649DP2010-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    12. Szymon Borak & Adam Misiorek & Rafał Weron, 2010. "Models for Heavy-tailed Asset Returns," SFB 649 Discussion Papers SFB649DP2010-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Beare, Brendan K., 2011. "Measure preserving derivatives and the pricing kernel puzzle," Journal of Mathematical Economics, Elsevier, vol. 47(6), pages 689-697.
    14. Enno Mammen & Christoph Rothe & Melanie Schienle, 2010. "Nonparametric Regression with Nonparametrically Generated Covariates," SFB 649 Discussion Papers SFB649DP2010-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Denis Belomestny & Shujie Ma & Wolfgang Karl Härdle, 2015. "Pricing Kernel Modeling," SFB 649 Discussion Papers SFB649DP2015-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    16. Ralf Sabiwalsky, 2010. "Executive Compensation Regulation and the Dynamics of the Pay-Performance Sensitivity," SFB 649 Discussion Papers SFB649DP2010-051, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    17. Carolin Hecht & Katja Hanewald, 2010. "Sociodemographic, Economic, and Psychological Drivers of the Demand for Life Insurance: Evidence from the German Retirement Income Act," SFB 649 Discussion Papers SFB649DP2010-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. 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.
    19. 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.
    20. Horatio Cuesdeanu & Jens Carsten Jackwerth, 2018. "The pricing kernel puzzle: survey and outlook," Annals of Finance, Springer, vol. 14(3), pages 289-329, August.
    21. 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.
    22. Vladimir Panov, 2010. "Estimation of the signal subspace without estimation of the inverse covariance matrix," SFB 649 Discussion Papers SFB649DP2010-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    23. 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.
    24. Maria Grith & Volker Krätschmer, 2010. "Parametric estimation of risk neutral density functions," SFB 649 Discussion Papers SFB649DP2010-045, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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    More about this item

    Keywords

    empirical pricing kernel; confidence band; bootstrap; kernel smoothing; nonparametric fitting;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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