We examine the impact of staggered high-speed rail (HSR) connection events between city pairs in China on retail investor behavior and stock market equilibrium outcomes. We find that HSR introductions between investor-firm city pairs promote intercity retail block purchases and cross-city web searches, and increase return comovement among firms in connected cities. Enhanced city connectivity is associated with improved firm valuation, increased turnover, better liquidity, and reduced prevalence of large trades. These effects tend to be driven by connected city pairs with a distance below 1,500 km, for which HSR is faster than flying.

Using a large sample of Chinese firms over the period of 2004–2017, this study investigates whether and how local corruption affects stock price crash risk. We find that firms headquartered in regions with higher levels of corruption tend to have higher future stock price crash risk. This relation is more pronounced for local state-owned enterprises (SOEs), and local corruption induces crash risk by pushing firms to engage in inefficient over-investment. Our results suggest that corruption induces managers to undertake value-destroying projects and withhold bad news, which will lead to an accumulation of bad news. As the bad news or bad performance accumulates and reaches a tipping point, a large amount of negative firm-specific information comes out, resulting in a crash. The findings enrich the understanding of local corruptions' microeconomic impact on firm's investment decisions and also contribute to the study of external factors that do influence crash risk.

Using the turnover decomposition model, we extract unexpected trading volume from trading activity to measure divergence in investors' opinions and explore the explanatory power of that divergence on stock returns. Portfolios built according to the magnitude of opinion divergence are significantly profitable. The expected returns of portfolios with small opinion divergence are significantly higher than other portfolios, particularly for small companies. When this pricing factor is included in the CAPM and the Fama–French three-factor model, the influence of opinion divergence on stock returns during the current month is significantly positive, but it is significantly negative for the next month. When further considering liquidity, momentum reversal and other factors, the conclusion is still valid.

Purpose – The purpose of this paper is to identify the effective measures for heterogeneity and to uncover the relationship between investor heterogeneity and stock returns. Design/methodology/approach – The paper employs dispersion in analysts’ earnings forecasts and unexpected trading volume as proxies of heterogeneity. Portfolio strategies and Fama-Macbeth regression are used to uncover the relationship between the two proxies and stock returns in the Chinese A-share market. Findings – The result indicates that stock returns are significantly related to unexpected trading volume, i.e., higher unexpected trading volume implies higher stock returns now but lower future stock returns. In contrast, there is no statistically significant relationship between analysts’ forecast dispersion and stock returns. Originality/value – The findings suggest that unexplained trading volume is an effective measure for investor heterogeneity in the Chinese A-share market.