Abstract

http://ssrn.com/abstract=2164379
 
 

Footnotes (26)



 


 



Can Analysts Assess Fundamental Risk and Valuation Uncertainty? An Empirical Analysis of Scenario-Based Value Estimates


Peter R. Joos


Morgan Stanley

Joseph D. Piotroski


Stanford Graduate School of Business

Suraj Srinivasan


Harvard Business School

September 19, 2012


Abstract:     
We use a dataset of sell-side analysts' scenario-based valuation estimates to examine whether analysts reliably assess the risk surrounding a firm’s fundamental value. We find that the spread in analysts’ state-contingent valuations captures the riskiness of operations and predicts the absolute magnitude of future long-run valuation errors and changes in firm fundamentals. Similarly, asymmetry embedded in the analysts’ scenario-based valuations conveys information about asymmetric risk-reward exposure and predicts skewness in future long-run valuation errors; however, embedded asymmetry is not correlated with changes in fundamentals. The results confirm that analysts’ valuations reflect both state-contingent risk assessments and non-fundamental factors.

Number of Pages in PDF File: 49

Keywords: Valuation, Analyst Forecasts, Scenarios, Uncertainty

JEL Classification: G13, G24, G30, M41

working papers series


Download This Paper

Date posted: October 20, 2012 ; Last revised: October 8, 2013

Suggested Citation

Joos, Peter R. and Piotroski, Joseph D. and Srinivasan, Suraj, Can Analysts Assess Fundamental Risk and Valuation Uncertainty? An Empirical Analysis of Scenario-Based Value Estimates (September 19, 2012). Available at SSRN: http://ssrn.com/abstract=2164379 or http://dx.doi.org/10.2139/ssrn.2164379

Contact Information

Peter R. Joos
Morgan Stanley ( email )
London
United Kingdom
Joseph D. Piotroski
Stanford Graduate School of Business ( email )
518 Memorial Way
Stanford, CA 94305-5015
United States

Suraj Srinivasan (Contact Author)
Harvard Business School ( email )
Soldiers Field
Boston, MA 02163
United States
HOME PAGE: http://drfd.hbs.edu/fit/public/facultyInfo.do?facInfo=pub&facId=10700
Feedback to SSRN


Paper statistics
Abstract Views: 1,782
Downloads: 630
Download Rank: 21,195
Footnotes:  26

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo2 in 0.437 seconds