Learning-Induced Securities Price Volatility

This file is part of IDEAS, which uses RePEc data

Learning-Induced Securities Price Volatility

Author Info

Peter Bossaerts

Additional information is available for the following registered author(s):

Peter L. Bossaerts

Abstract

This paper tests whether the high average returns on the S&P 500 index in recent history can be attributed to mistaken expectations (the ex-ante risk premium -- taken to be constant -- is systematically less than the ex-post measured risk premium), or, alternatively, whether can they be explained as the result of selection bias (the U.S. experience is exceptional). The tests reject these hypotheses over the periods 1/81 to 12/97 (p = 0.02), and 1/41-12/60 (p = 0.03). They do not reject over the periods 1/28-12/40 and 1/61-12/80. The tests are based on a bound that the ex-post Sharpe ratios impose on the volatility of the ratio of the market's prior and posterior beliefs about future outcomes. The bound derives from a property of Bayesian learning first noted in an earlier paper. Qualitatively, for the bound not to be violated, higher absolute mean excess returns may need to be accompanied with higher volatility. This should be interpreted as predicting that large price movements (positive as well as negative) may have to be erratic. We confirm this prediction for the S&P 500 data.

Download Info
To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" 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 search for a similarly titled item that would be available.

Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 299.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length:
Date of creation: 05 Jul 2000
Date of revision:
Handle: RePEc:sce:scecf0:299

Contact details of provider:
Postal: CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain
Fax: +34 93 542 17 46
Email:
Web page: http://enginy.upf.es/SCE/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords:

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

Larry Epstein & Martin Schneider, 2005. "Ambiguity, Information Quality and Asset Pricing," RCER Working Papers 519, University of Rochester - Center for Economic Research (RCER). [Downloadable!]
Other versions:
- Larry Epstein & Martin Schneider, 2004. "Ambiguity, Information Quality and Asset Pricing," RCER Working Papers 507, University of Rochester - Center for Economic Research (RCER). [Downloadable!]
- Larry G. Epstein & Martin Schneider, 2008. "Ambiguity, Information Quality, and Asset Pricing," Journal of Finance, American Finance Association, vol. 63(1), pages 197-228, 02. [Downloadable!] (restricted)
Larry Epstein & Martin Schneider, 2002. "Learning Under Ambiguity," RCER Working Papers 497, University of Rochester - Center for Economic Research (RCER), revised Mar 2005. [Downloadable!]
Other versions:
- Larry Epstein & Martin Schneider, 2006. "Learning Under Ambiguity," RCER Working Papers 527, University of Rochester - Center for Economic Research (RCER). [Downloadable!]
- Larry G. Epstein & Martin Schneider, 2007. "Learning Under Ambiguity," Review of Economic Studies, Blackwell Publishing, vol. 74(4), pages 1275-1303, October. [Downloadable!] (restricted)

Statistics

Access and download statistics

Did you know? You too can volunteer for RePEc, for example by encouraging others to use our services.

This page was last updated on 2008-12-2.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.