Investment decision-making in the information-return space

In this paper, I examine the value that investors place on analysts who exhibit lower forecast error volatility. Building on prior empirical research, I develop a theoretical model that formalizes the role of error volatility in investment decision-making. I propose an investment strategy that leverages analysts' forecasts, acknowledging the challenges associated with distinguishing report quality, which can be costly in terms of time, money, and cognitive effort. The study focuses on a stock market with heterogeneous investors, where rational informed investors must screen reports of varying quality. I find that, when applying a screening rule à la Anderson and Renault (1999), informed investors incorporate both the news and the volatility of forecast errors, preferring more consistent reports for similar signals. These findings enhance understanding of how investors navigate information uncertainty and highlight the practical significance of the methodology for investment management.