Title

Understanding Analysts Forecasts

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

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.