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Pricing Kernel Monotonicity and Conditional Information

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  • Matthew Linn
  • Sophie Shive
  • Tyler Shumway

Abstract

A large literature finds evidence that pricing kernels nonparametrically estimated from option prices and historical returns are not monotonically decreasing in market index returns. We argue that existing estimation methods are inconsistent and propose a new nonparametric estimator of the pricing kernel that reflects the information available to investors who set asset prices. In simulations, the estimator outperforms existing techniques. Our empirical estimates using S&P 500 index option data from 1996 to 2014 and FTSE 100 index option data from 2002 to 2014 suggest that the “pricing kernel puzzle” is due to flaws in existing estimators rather than a behavioral or economic phenomenon. Received August 2, 2015; editorial decision April 15, 2017 by Editor Andrew Karolyi.

Suggested Citation

  • Matthew Linn & Sophie Shive & Tyler Shumway, 2018. "Pricing Kernel Monotonicity and Conditional Information," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 493-531.
    • Handle: RePEc:oup:rfinst:v:31:y:2018:i:2:p:493-531.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhx095
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    Citations

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    Cited by:

    1. Brendan K. Beare & Juwon Seo & Zhongxi Zheng, 2022. "Stochastic arbitrage with market index options," Papers 2207.00949, arXiv.org, revised May 2024.
    2. Steven Heston & Kris Jacobs & Hyung Joo Kim, 2023. "The Pricing Kernel in Options," Finance and Economics Discussion Series 2023-053, Board of Governors of the Federal Reserve System (U.S.).
    3. Gagnon, Marie-Hélène & Power, Gabriel J. & Toupin, Dominique, 2023. "The sum of all fears: Forecasting international returns using option-implied risk measures," Journal of Banking & Finance, Elsevier, vol. 146(C).
    4. 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.
    5. Jiao, Yuhan & Liu, Qiang & Guo, Shuxin, 2021. "Pricing kernel monotonicity and term structure: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 123(C).
    6. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.
    7. Maik Dierkes & Jan Krupski & Sebastian Schroen & Philipp Sibbertsen, 2024. "Volatility-dependent probability weighting and the dynamics of the pricing kernel puzzle," Review of Derivatives Research, Springer, vol. 27(1), pages 1-35, April.
    8. Hammad Siddiqi & Sajid Anwar, 2020. "The Pricing Kernel Puzzle: A Real Phenomenon or a Statistical Artifact?," International Review of Finance, International Review of Finance Ltd., vol. 20(2), pages 485-491, June.
    9. 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.

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