Information Frictions and Stock Returns

Xiaolou Yang

doi:10.3390/jrfm13070140

Abstract

The purpose of this paper is to assess the impact of ambiguity on financial analyst forecast incentives and the associated abnormal stock returns. I present a model incorporating ambiguity aversion into a two-period Lucas tree model. The resulting model confirms the role of ambiguity in the determination of asset returns. In particular, the model with ambiguity aversion generates a lower price and a higher required rate of returns compared to the classical model without ambiguity concern. I construct a measure of ambiguity and provide empirical evidence showing that the incentive of analysts to misrepresent information is a function of ambiguity. Analysts are more likely to bias their forecasts when it is more difficult for investors to detect their misrepresentation. Under ambiguity, analysts’ optimistic forecasts for good/bad news tend to deteriorate. Moreover, stock returns are positively related with ambiguity. Under ambiguity neither good nor bad news is credible. Investors systematically underreact to good news forecast and overreact to bad news forecast when ambiguity exists.

Highlights

The literature on financial analyst forecast defines “forecast inefficiency” as forecasts that fail to accurately incorporate new information on a timely basis
It confirms the fact that by ignoring ambiguity, conventional measures of risk aversion underestimate the effect of uncertainty on asset prices
According to the t-test, forecast errors and stock returns are significantly different between the forecasts with ambiguity and those with no ambiguity

Summary

Introduction

The literature on financial analyst forecast defines “forecast inefficiency” as forecasts that fail to accurately incorporate new information on a timely basis. It confirms the fact that by ignoring ambiguity, conventional measures of risk aversion underestimate the effect of uncertainty on asset prices This result can be used to explain why investors appear to overreact/underreact to small probability events. Analysts’ optimistic forecasts for good/bad news tend to deteriorate These results provide evidence showing that financial analysts forecast errors are to be underestimated when ignoring ambiguity. This equation indicates the effects on ambiguity for a unit increase in asset holding This equation helps explain both the risk-free rate puzzle and the equity premium puzzle. If β is sufficiently large relative to α, the effect through the variance will dominate, and dφ dθn will be positive In this case, ambiguity will reduce the price of stocks and increase their return relative to the standard model. Ambiguity complements risk aversion in our discussion of the risk-free rate puzzle and the equity premium puzzle

Hypothesis Development

Empirical Analysis

Discussions and Conclusions