This paper represents the first attempt to show how heterogeneous shock experiences help explain the enduring scars on household future behaviors. Using a large-scale household survey with 15,652 observations combined with geospatial transportation big data, we identify a novel belief-updating mechanism through which crises may exert prolonged impacts on household asset allocation and consumption patterns. An increase in the duration of previous lockdown experience is associated with a 10.52% escalation in enhanced anxiety for future precautionary saving motivations. This experience-based learning perspective supports the resolution of long-lasting overreactions to negative shocks via belief revisions and extends to households’ consumption behaviors. The lingering effects continue to skew households' beliefs even when conditions improve. Additionally, households with different individual-based shock experiences may exhibit varying perceptions of external shocks, resulting in disparate belief revision processes.

In forecast surveys of aggregate macroeconomic and financial variables, the correlation between forecast errors and forecast revisions is positive at the consensus level, but negative at the individual level. Past literature has interpreted this discrepancy as evidence of underreaction to news at the aggregate level and overreaction at the individual level. In this paper, I challenge this view by arguing that noise in predictive judgment can account for the difference. Using a stylized model, I examine how introducing judgment noise at the individual level changes the interpretation of the correlation coefficients. First, a negative coefficient at the individual level no longer necessarily means overreaction. Second, the coefficient at the consensus level underestimates the degree of underreaction. Using forecast survey data, I provide evidence that judgment noise is large enough to reconcile the difference between the two coefficients. The structural parameter measuring over-/underreaction mainly points to underreaction, regardless of whether the model matches correlation coefficients at the individual or aggregate level.

Using novel data from a stock forum, we analyze return extrapolation in the cross-section. Our findings indicate that extrapolators overreact to the returns but underreact to the fundamentals. The post-earnings-announcement drift (PEAD) is more pronounced among firms with a high firm-level degree-of-extrapolation (DOX). Additionally, investors ask fewer questions about high-DOX firms’ fundamental information on official online interactive platforms. Extrapolation reduces the informativeness of stocks due to investors’ inattention to fundamentals. Furthermore, extrapolators’ overreaction to returns and underreaction to fundamentals increase stock price crash risks. These findings support explanations of extrapolation based on limited asymmetric attention.

While the vast majority of the literature reports momentum profitability to be overwhelming in the U.S. market and widespread in other countries, this paper finds that the pure momentum strategy in general does not yield excess profitability in the Chinese stock markets. We find instead strong mean reversion with an average half-life slightly shorter than one year. A pure contrarian investment strategy produces positive excess returns and in general outperforms the pure momentum strategy. Furthermore, momentum may interact with mean reversion. A strategy based on the rolling-regression parameter estimates of the model combining mean reversion and momentum generates both statistically and economically significant excess returns. The combined strategy outperforms both pure momentum and pure contrarian strategies. We conduct a number of robustness tests and confirm the basic findings. Collectively, our results seem to support the overreaction hypothesis.