Publication Type
Journal Article
Version
Postprint
Publication Date
2010
Abstract
The purpose of this paper is to model analysts’ forecasts. The paper differs from the previous research in that we do not focus on how accurate these predictions may be. Accuracy may indeed be an important quality but we argue instead that another equally important aspect of the analysts’ job is to predict and describe the impact of jump events. In effect, the analysts’ role is one of scenario prediction. Using a Bayesian-inspired generalised method of moments estimation procedure, we use this notion of scenario prediction combined with the structure of the Morgan Stanley analysts’ forecasting database to model normal (base), optimistic (bull) and pessimistic (bear) forecast scenarios for a set of reports from Asia (excluding Japan) for 2007–2008. Since the estimation procedure is unique to this paper, a rigorous derivation of the asymptotic properties of the resulting estimator is also provided.
Keywords
analysts’ reports, price forecasts, scenario prediction, jump diffusions, risk management
Discipline
Accounting | Portfolio and Security Analysis
Research Areas
Financial Intermediation and Information
Publication
European Journal of Finance
Volume
16
Issue
2
First Page
97
Last Page
118
ISSN
1351-847X
Identifier
10.1080/13518470902853582
Publisher
Taylor and Francis
Embargo Period
3-7-2014
Citation
Louth, R. J.; Joos, P.; Satchell, S. E.; and Weyns, Guy.
Understanding Analysts Forecasts. (2010). European Journal of Finance. 16, (2), 97-118.
Available at: https://ink.library.smu.edu.sg/soa_research/1184
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/13518470902853582