Filtering Returns for Unspecified Biases in Priors when Testing Asset PricingTheory
AbstractProcedures are presented that allow the empiricist to estimate and test asset pricing models on limited-liability securities without the assumption that thehistorical payoff distribution provides a consistent estimate of the market's priorbeliefs. The procedures effectively filter return data for unspecified historical biases in the market's priors. They do not involve explicit estimation of the market's priors, and hence, economize on parameters. The procedures derive from a new but simple property of Bayesian learning, namely: if the correct likelihood is used, the inverse posterior at the true parameter value forms a martingale process relative to the learner's information filtration augmented with the true parameter value. Application of this central result to tests of asset pricing models requires a deliberate selection bias. Hence, as a by-product, the article establishes that biased samples contain information with which to falsify an asset pricing model or estimate its parameters. These include samples subject to, "e.g." survivorship bias or Peso problems. Copyright The Review of Economic Studies Limited, 2004.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Wiley Blackwell in its journal Review of Economic Studies.
Volume (Year): 71 (2004)
Issue (Month): 1 (01)
Contact details of provider:
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0034-6527
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Adam, Klaus & Marcet, Albert & Nicolini, Juan Pablo, 2007.
"Stock Market Volatility and Learning,"
CEPR Discussion Papers
6518, C.E.P.R. Discussion Papers.
- Adam, Klaus & Marcet, Albert & Nicolini, Juan Pablo, 2012. "Stock Market Volatility and Learning," Working Papers 12-06, University of Mannheim, Department of Economics.
- Albert Marcet & Klaus Adam & Juan Pablo Nicolini, 2008. "Stock Market Volatility and Learning," UFAE and IAE Working Papers 732.08, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
- Adam, Klaus & Marcet, Albert & Nicolini, Juan Pablo, 2008. "Stock market volatility and learning," Working Paper Series 0862, European Central Bank.
- Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2011. "Stock Market Volatility and Learning," CEP Discussion Papers dp1077, Centre for Economic Performance, LSE.
- Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2008. "Stock Market Volatility and Learning," Working Papers 336, Barcelona Graduate School of Economics.
- Cogley, Timothy & Sargent, Thomas J., 2008. "The market price of risk and the equity premium: A legacy of the Great Depression?," Journal of Monetary Economics, Elsevier, vol. 55(3), pages 454-476, April.
- Chen, Anlin & Chiou, Sue L. & Wu, Chinshun, 2004. "Efficient learning under price limits: evidence from IPOs in Taiwan," Economics Letters, Elsevier, vol. 85(3), pages 373-378, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
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 references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.