A Market Model of Analysts' Opinions to Explain Changes in the Dispersion of Opinions

By Benrud, Erik | Journal of Economics and Finance, Summer 2007 | Go to article overview

A Market Model of Analysts' Opinions to Explain Changes in the Dispersion of Opinions


Benrud, Erik, Journal of Economics and Finance


Abstract

The demand for and supply of analysts' opinions in this model yield an equilibrium that demonstrates how the information content of the opinions reacts to changes in exogenous parameters. The model also shows how changes in the parameters make analysts' opinions more or less dispersed; for example, a decline in investor risk aversion, a decrease in market volatility, and an increase in information costs can lead to analysts' opinions becoming more similar. Recognizing how exogenous factors can affect the supply and demand of analysts' opinions gives additional insights into questions concerning what may appear to be herd behavior by analysts and also the relationship between forecast dispersion and information content.

(JEL: G29, C71)

Introduction

This paper develops from first principles a demand for and a supply of analysts' opinions where the buyers use the opinions in the investment process. The goal is to develop a model that can help explain the changing levels of information content and dispersion of those opinions. On a more general level, the model is valuable because it presents a framework for analyzing how information sellers and buyers in the financial services market interact and the effect this has on the quality of products provided; furthermore, such a model is needed given changes initiated by such actions as Regulation Fair Disclosure. As a specific application of the model, I demonstrate how exogenous variables such as the cost of information and investor preferences can make the analysts' opinions more or less similar, which gives additional insights into phenomena that is often attributed to the desire of analysts to engage in herd behavior. The paper concludes with a summary of how the theoretical results of the model are congruent with empirical relationships observed in the herd behavior literature.

There is clearly a need for a model that includes a variety of inputs to explain the behavior of analysts. This is because research on analysts' opinions has often produced conflicting results. There is a controversy, for example, as to whether the level of forecast dispersion is an indicator of the amount of information in the forecasts and their accuracy. There is also a controversy as to whether analysts engage in herd behavior. Herd behavior describes a situation where an analyst ignores some or all of his/her private information and gives an opinion or engages in an action that is similar to the majority of other analysts (see Scharfstein and Stein, 1990). According to some researchers, various factors influence the desire to herd. For example, Graham (1999) found that "a newsletter analyst is likely to herd on Value Line's recommendation if her reputation is high, if her ability is low, or if signal correlation is high." (p. 237). The model here demonstrates how inputs like the cost of information and the demand function of opinion purchasers in a competitive market can explain changes in the dispersion of opinions, and those changes in dispersion are based only on the amount of information that the analysts determine it is optimal to obtain.

In the model, analysts engage in quality differentiation and sell their opinions to buyers who are investors with varying levels of risk aversion. The model includes a cost of information function that has the available amount of free-information and the marginal cost of additional information as its arguments. The model recognizes that the price a buyer is willing to pay the analyst will depend upon that buyer's willingness to use the opinion, and in an investment setting, that will depend upon that buyer's level of risk aversion. The resulting demand function, in turn, influences the amount of information analysts gather.

On the demand side, each buyer has a unique level of risk aversion as measured by a single parameter. The distribution of the risk aversion parameter may change from period to period, which influences the market demand function, and this will change the amount of information that is optimal for the analysts to gather each period. …

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