Summary:
The Chinese stock market, characterized by rapid expansion, high retail investor participation, significant information asymmetry, and substantial volatility, frequently exhibits overreaction phenomena. Financial analysts, as key information intermediaries, play a crucial role in shaping market-wide expectations. This study investigates their overreaction through the novel diagnostic expectations theory. Rooted in the psychological concept of “representativeness,” this theory argues that individuals, when interpreting new information, overweight outcomes that are more representative of a given state. This cognitive shortcut leads to systematic prediction errors and overreaction, a behavior particularly relevant in China's uncertain and competitive market environment, where analysts may be encouraged to rely on such heuristics. This research, therefore, aims to quantify this bias and explore its implications for asset prices and market sentiment. To enhance the reliability of our estimation, this paper refines the existing Simulated Method of Moments (SMM) methodology for quantifying the degree to which an analyst's judgment is distorted by the representativeness heuristic. Our primary methodological contributions are twofold. First, we introduce a Block-Bootstrap procedure to construct confidence intervals for the estimated parameters. This non-parametric approach addresses the potential non-normal distribution of parameter estimates and strengthens the statistical robustness of our findings. Second, to mitigate the subjective bias associated with specific moment condition selection for the estimation, we systematically traverse all possible combinations of valid moment conditions. This ensures that our results are not contingent on an arbitrary choice of model specifications, thereby providing a more robust and statistically sound estimate of the diagnostic expectations parameter in China. Our research yields several key findings. We find strong evidence of overreaction among Chinese stock market analysts. The baseline estimation for the key parameter measuring this bias is not only statistically significant but also more than double the value estimated for the U.S. market, indicating a substantially stronger influence of this cognitive bias in China. The bias is more pronounced for firms with higher risk profiles, specifically those with poor liquidity, high financial leverage, and low institutional ownership. After decomposing forecasts into a rational component and a bias component, we find this bias has significant economic consequences. It drives a time-varying relationship with future stock returns, where a long-term negative correlation is consistent with the classic overreaction hypothesis and subsequent price reversal. Moreover, the bias exhibits an inverted U-shaped relationship with future market sentiment, with the effect being more pronounced and rapid in online media compared to traditional print media. This study makes several contributions to the literature. First, it enhances the estimation of the diagnostic expectations model by incorporating Block-Bootstrap and a systematic traversal of moment conditions, improving the robustness and reliability of the empirical results. Second, it provides strong evidence for the applicability of diagnostic expectations theory in the Chinese context, a crucial emerging market, quantifying a key behavioral bias that drives analyst behavior. Most importantly, by decomposing forecasts and linking the bias component to subsequent market outcomes, it offers a novel channel for understanding the relationship between analyst cognitive biases, long-term stock return predictability, and the dynamics of market sentiment. These findings provide valuable insights into understanding overreaction for investors seeking investment strategies and for regulators concerned with market stability.
张一帆, 林建浩, 林伊漩. 推断预期视角下中国股票市场分析师的过度反应研究[J]. 金融研究, 2025, 546(12): 151-168.
ZHANG Yifan, LIN Jianhao, LIN Yixuan. Overreaction of Analysts in the Chinese Stock Market from the Perspective of Diagnostic Expectations. Journal of Financial Research, 2025, 546(12): 151-168.
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