IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v21y2008i1p181-231.html
   My bibliography  Save this article

Conditioning Information and Variance Bounds on Pricing Kernels with Higher- Order Moments: Theory and Evidence

Author

Listed:
  • Fousseni Chabi-Yo

Abstract

We develop a strategy for utilizing higher moments, variance risk premia, and conditioning information efficiently, and hence improve on the variance bounds computed by Hansen and Jagannathan (1991); Gallant, Hansen, and Tauchen (1990); and Bekaert and Liu (2004). Our bounds reach existing bounds when nonlinearities in returns are not priced. We also use higher moments, variance risk premia, and conditioning information to provide distance measures that improve on the Hansen and Jagannathan (1997) distance measure. Empirical results indicate that when accounting for the impact of higher moments and variance risk premia, the existing pricing kernels have difficulty in explaining returns on the assets and derivatives. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Fousseni Chabi-Yo, 2008. "Conditioning Information and Variance Bounds on Pricing Kernels with Higher- Order Moments: Theory and Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 181-231, January.
    • Handle: RePEc:oup:rfinst:v:21:y:2008:i:1:p:181-231
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rfs/hhm053
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Lin, Yuehao & Lehnert, Thorsten & Wolff, Christian, 2019. "Skewness risk premium: Theory and empirical evidence," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 174-185.
    2. Peñaranda, Francisco & Sentana, Enrique, 2016. "Duality in mean-variance frontiers with conditioning information," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 762-785.
    3. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    4. Caio Almeida & René Garcia, 2017. "Economic Implications of Nonlinear Pricing Kernels," Management Science, INFORMS, vol. 63(10), pages 3361-3380, October.
    5. Geert Bekaert & Eric Engstrom & Andrey Ermolov, 2023. "The Variance Risk Premium in Equilibrium Models," Review of Finance, European Finance Association, vol. 27(6), pages 1977-2014.
    6. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    7. Yuewu Xu, 2021. "A new measure of model misspecification with the no-arbitrage constraint: extending the second Hansen–Jagannathan distance," Review of Quantitative Finance and Accounting, Springer, vol. 56(3), pages 917-938, April.
    8. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
    9. Wonnho Choi, 2018. "Consumption-based capital asset pricing models: issues and controversies," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 181-205, January.
    10. Abed Masrorkhah, Sara & Lehnert, Thorsten, 2017. "Press freedom and jumps in stock prices," Economic Systems, Elsevier, vol. 41(1), pages 151-162.
    11. Xu, Yuewu & Yao, Xiangkun, 2019. "Extending the Hansen–Jagannathan distance measure of model misspecification," Finance Research Letters, Elsevier, vol. 29(C), pages 384-392.
    12. Bruno Feunou & Mohammad R Jahan-Parvar & Cédric Okou, 2018. "Downside Variance Risk Premium," Journal of Financial Econometrics, Oxford University Press, vol. 16(3), pages 341-383.
    13. Winston Buckley & Sandun Perera, 2019. "Optimal demand in a mispriced asymmetric Carr–Geman–Madan–Yor (CGMY) economy," Annals of Finance, Springer, vol. 15(3), pages 337-368, September.
    14. Belén Nieto & Alfonso Novales Cinca & Gonzalo Rubio, 2011. "Variance Swaps and Intertemporal Asset Pricing," Documentos de Trabajo del ICAE 2011-08, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

    More about this item

    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:oup:rfinst:v:21:y:2008:i:1:p:181-231. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sfsssea.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.