IDEAS home Printed from https://ideas.repec.org/p/rza/ersawp/390.html

Biased Bayesian Learning with an Application to the Risk-Free Rate Puzzle

Author

Listed:
  • Alexander Ludwig
  • Alexander Zimper

Abstract

Based on the axiomatic framework of Choquet decision theory, we develop a closed-form model of Bayesian learning with ambiguous beliefs about the mean of a normal distribution. In contrast to rational models of Bayesian learning the resulting Choquet Bayesian estimator results in a long-run bias that reflects the agent's ambiguity attitudes. By calibrating the standard equilibrium conditions of the consumption based asset pricing model we illustrate that our approach contributes towards a resolution of the risk-free rate puzzle. For a plausible parameterization we obtain a risk-free rate in the range of 3.5-5 percent. This is 1-2.5 percent closer to the empirical risk-free rate than according calibrations of the rational expectations model.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Alexander Ludwig & Alexander Zimper, 2013. "Biased Bayesian Learning with an Application to the Risk-Free Rate Puzzle," ERSA Working Paper Series 390, Economic Research Southern Africa.
    • Handle: RePEc:rza:ersawp:390
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Craig Webb, 2015. "Piecewise additivity for non-expected utility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 60(2), pages 371-392, October.
    3. Alexander Ludwig & Alexander Zimper, 2013. "A decision-theoretic model of asset-price underreaction and overreaction to dividend news," Annals of Finance, Springer, vol. 9(4), pages 625-665, November.
    4. Albrecht, E & Baum, Günter & Birsa, R & Bradamante, F & Bressan, A & Chapiro, A & Cicuttin, A & Ciliberti, P & Colavita, A & Costa, S & Crespo, M & Cristaudo, P & Dalla Torre, S & Diaz, V & Duic, V &, 2010. "Results from COMPASS RICH-1," Center for Mathematical Economics Working Papers 535, Center for Mathematical Economics, Bielefeld University.
    5. repec:rza:wpaper:296 is not listed on IDEAS
    6. repec:rza:wpaper:240 is not listed on IDEAS
    7. Alexander Zimper & Wei Ma, 2017. "Bayesian learning with multiple priors and nonvanishing ambiguity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 64(3), pages 409-447, October.
    8. Craig S. Webb, 2017. "Piecewise linear rank-dependent utility," Theory and Decision, Springer, vol. 82(3), pages 403-414, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:rza:ersawp:390. 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: Maggi Sigg (email available below). General contact details of provider: https://ersawps.org/index.php/working-paper-series/ .

    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.