The Impacts of Fragmented Volatilities by Learning about Predictability in the Real Options Approach
This paper examines the effects of uncertainty through dynamic learning about the firm's project value in the real options framework. We extend the real options framework with incomplete information by allowing an unobserved state variable that drives profits to follow a stochastic process with market uncertainty. Similar to the proposition in the standard real options approach where complete information is available, we find that in the situation with incomplete information the project value increases as the market uncertainty increases. Furthermore, we demonstrate that the project value increases as both information uncertainty decreases and estimation uncertainty increases
To our knowledge, this item is not available for
download. To find whether it is available, there are three
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.
|Date of creation:||11 Aug 2004|
|Date of revision:|
|Contact details of provider:|| Web page: http://comp-econ.org/|
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:sce:scecf4:255. 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: (Christopher F. Baum)
If references are entirely missing, you can add them using this form.