We examine the influence of foreign equity flows on China's unique retail-dominated stock market, identifying a novel channel through which investors’ herding creates significant market externalities. We find that the daily disclosure of foreign investors' positions induces local investors to imitate these trades, resulting in observable short-term price distortions followed by reversals. Our analyses, which include inflow predictability tied to disclosure timing and path analysis decomposition, confirm that the herding effect, largely driven by retail participants, is more impactful than the direct effect based on the informational content of foreign capital. Furthermore, inflated stock prices resulting from the herding behavior cause public firms to overvalue and overinvest, leading to reduced investment efficiencies. These findings highlight potential adverse consequences stemming from specific stock market liberalization designs.

We examine price discovery after irregularly scheduled macroeconomic announce-ments. Exploiting time variation in Chinese macro announcements released outside regular trading hours, this paper isolates the role of elapsed non-trading time in facilitating investor learning and price discovery upon market reopening. We show that longer non-trading intervals generate more efficient post-announcement price discovery, reduce information asymmetry, and diminish subsequent intraday return reversals. The mechanism operates through enhanced retail investor learning: during non-trading hours, retail investors actively acquire information, subsequently trade more aggressively, earn higher profits, and face reduced informational disadvantages at market opening. Our findings highlight that retail investor learning during non-trading hours levels the informational playing field among heterogeneous investors and improves price quality around irregularly timed macroeconomic announcements. These results have broader implications for emerging markets, which similarly feature irregular announcement timing and large populations of uninformed retail investors.

We propose the AI Narrative Gap as a novel firm characteristic—the systematic divergence between a firm’s AI strategic narrative intensity and its subsequent AI capital expenditure commitment—and document its capital market consequences. Using Chinese A-share listed firms from 2015 to 2022, we show that firms with a wider AI Narrative Gap attract significantly more optimistic and less accurate analyst earnings forecasts. These distorted expectations, in turn, predict lower subsequent stock returns, lower industry-adjusted abnormal returns, and weaker future accounting performance. A double-sort portfolio placing firms simultaneously in the highest tercile of the AI Narrative Gap and highest tercile of analyst optimism earns a mean return 22.8 percentage points below that of the lowest tercile on both dimensions (t = −5.10). The return reduction in the AI Narrative Gap coefficient is attenuated but not eliminated after controlling for optimism, consistent with a partial expectation-distortion channel. Collectively, these results establish the AI Narrative Gap as a cross-sectionally informative firm characteristic that captures the credibility of a firm’s AI strategic identity, with systematic implications for analyst expectations and asset prices.

The flow-performance relation in China’s mutual fund market differs from that in developed markets (e.g., the U.S.). We find that investors actively allocate capital to poorly performing funds, generating a negative relation at the bottom of return distribution. These flows are driven mainly by increased purchases rather than reduced redemptions. We then examine the mechanisms behind this anomaly. First, investors act on rational expectations of performance reversals, with this pattern being more pronounced among funds with higher activeness. Second, product differentiation attracts heterogeneous investors when performance is weak. Third, marketing and fund family effects serve as simple signals that amplify inflows. Overall, our study provides new empirical evidence on fund investor behavior and its economic consequences in an emerging market context.

We introduce a real-time dispersion measure based on cross-sectional stock returns explicitly designed to capture retail-driven speculative episodes. Elevated return dispersion effectively identifies periods characterized by intensified retail investor trading behaviors, driven by salience, diagnostic expectations, and extrapolative beliefs. During these high-dispersion states, momentum strategies collapse, and short-term reversals become dominant. Conditioning momentum strategies on our dispersion measure resolves the longstanding puzzle of missing momentum in retail-intensive markets such as China, substantially enhancing profitability. A dynamic rotation strategy between momentum and short-term reversal portfolios guided by dispersion states achieves annualized Sharpe ratios nearly double those of static approaches. Extending our analysis internationally, we employ Google search trends as proxies for retail investor attention, confirming that dispersion robustly predicts momentum and reversal returns globally. Our findings underscore the behavioral channel through which retail-driven speculation conditions momentum dynamics, providing clear implications for dynamic portfolio management strategies.

We investigate the relationship between the intensity of intraday return reversals and future stock returns in the Chinese stock market. We find that a high frequency of positive overnight returns followed by negative daytime returns predicts one-month ahead returns positively. The analysis shows that daytime retail investors tend to overly sell their own rising stocks at market open, accepting lower stock prices in exchange for liquidity. As the price pressure attenuates, these stocks experience subsequent price increases, implying a positive relationship between return reversals and future returns.

This study shows how price limit rules, intended to stabilize markets, inadvertently distort price dynamics by fostering strategic speculation. Through a dynamic rational expectations model, we demonstrate that price limits induce post limit-up price jumps by impeding full information incorporation, enabling speculators to artificially push prices to upper bounds and exploit uninformed traders. The model predicts two distinct patterns: (1) stocks closing at price limits exhibit positive overnight returns followed by long-term reversals, and (2) stocks retreating from upper bounds suffer sharp reversals with partial recovery. Empirical analysis confirms these predictions. A natural experiment from China’s 2020 GEM reform —- which widened the price limit -— further provides causal evidence that relaxed limits mitigate speculative distortions.

I conduct an exploratory study about the feasibility of factor timing in the Chinese stock market, covering 24 representative and well-identiffed risk factors in ten categories from the literature. The long-short portfolio of short-term reversal exhibits strong and statistically signiffcant out-of-sample predictability, which is robust across various models and all types of predictors. However, such results are not evident in the prediction of all other factors’ long-short portfolios, as well as all factors’ long-wing and short-wing portfolios. The high exposure to the market beta, together with the unpredictability of the market return, explains these failures to some degree. On the other hand, a simple investment strategy based on predicted returns of the reversal factor’s long-short portfolio obtains a signiffcant return three times higher than the simple buy-and-hold strategy in the sample period, with a signiffcant annualized 20.4% CH-3 alpha.

Why is price momentum absent in China? Since momentum is commonly considered arising from investors’ under-reaction to fundamental news, we decompose monthly stock returns into news- and non-news-driven components and document a news day return continuation along with an offsetting non-news day reversal in China. The non-news day reversal is particularly strong for stocks with high retail ownership, relatively less recent positive news articles, and limits to arbitrage. Evidence on order imbalance suggests that stock returns overshoot on news days due to retail investors' excessive attention-driven buying demands, and mispricing gets corrected by institutional investors on subsequent non-news days. To avoid this tug-of-war in stock price, we use a signal that directly captures the recent news performance and re-document a momentum-like underreaction to fundamental news in China.

We examine ESG pricing in the Chinese stock market. The results show that holding stocks with high ESG scores does not provide investors with higher future excess returns. On the contrary, stocks with low ESG scores perform better. However, this negative ESG premium feature is robust only in small-cap stocks. As size increases, the negative ESG premium fades away and is characterized by a positive premium in larger stock subgroups. We further examine the source of the negative ESG premium in small-cap stocks. The results show that this negative premium can not be explained by firm characteristics, short-term reversal effects, and lottery characteristics of stocks, but is associated with ESG investors. Specifically, the higher the ESG score with more ESG investors in small-cap stocks, the lower the expected excess return of the stock. This result implies that firms may benefit from ESG performance and disclosure, while investors may suffer from ESG strategies. Based on the results, we remind investors that they should be cautious in using ESG indicators to guide their investment decisions.