Behavioral Biases and Report Accuracy: An Empirical Study of Investment Analysts Across Global Markets

This research investigates the extent to which behavioral biases—specifically overconfidence and representativeness heuristic—affect linguistic tone, narrative structure, and predictive accuracy of financial reports produced by investment analysts operating across diverse global markets. Drawing upon a comprehensive dataset comprising 1575 equity recommendation reports authored by 15 analysts from four major international investment banks between 2019 and 2022, the study evaluates how cognitive tendencies shape report composition and forecast precision. A mixed-methods approach was employed, incorporating qualitative textual analysis and quantitative modeling through random-effects panel regressions. Key constructs assessed include narrative complexity, optimism, visual content usage, and forecast deviation metrics. Our findings reveal that overconfidence significantly influences the tone and detail of analyst reports but does not demonstrably impact projection accuracy. Conversely, representativeness heuristics were not found to consistently affect either report language or earnings-per-share forecast errors. Institutional affiliation emerged as a significant determinant of predictive success, while demographic factors such as gender, native language, and geographic region had limited explanatory power. These findings imply that investors should treat report tone as an indicator of analyst disposition rather than forecast quality, while financial institutions may benefit from training programs aimed at mitigating narrative and stylistic biases in analyst communication.