Learning and Asset-price Jumps
We develop a general equilibrium model in which income and dividends are smooth but asset prices contain large moves (jumps). These large price jumps are triggered by optimal decisions of investors to learn the unobserved state. We show that learning choice is determined by preference parameters and the conditional volatility of income process. An important model prediction is that income volatility predicts future jump periods, while income growth does not. Consistent with the model, large moves in returns in the data are predicted by consumption volatility but not by consumption growth. The model quantitatively captures these novel features of the data. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: email@example.com., Oxford University Press.
If 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.
Volume (Year): 24 (2011)
Issue (Month): 8 ()
|Contact details of provider:|| Postal: Oxford University Press, Journals Department, 2001 Evans Road, Cary, NC 27513 USA.|
Web page: http://www.rfs.oupjournals.org/
More information through EDIRC
|Order Information:||Web: http://www4.oup.co.uk/revfin/subinfo/|
When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:24:y:2011:i:8:p:2738-2780. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)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.