This paper reexamines the dynamic relation between intraday trading volume and return volatility of large and small NYSE stocks in two partitioned samples, with and without identifiable public news. We argue that the sequential information arrival hypothesis (SIAH) can be tested only in periods containing public news. After partitioning the sample into periods with and without public news, we find bi-directional Granger-causality between volume and volatility in the presence of public information as hypothesized by the SIAH. Our analysis further suggests that return volatility is higher in the periods with public news, while trading volume is significantly higher in the no-news period; perhaps owing to the importance of private information for trading stocks. Using the sample without public news, we find evidence that volume Granger-causes volatility without feedback. These results are broadly consistent with behavioral models like the overconfidence and biased self-attribution model of [Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and over-reactions. Journal of Finance 53, 1839–1885]. It appears that overconfident investors overrate the precision of their private news signals and therefore trade too aggressively in the absence of public news; when public news arrives, investors’ biased self-attribution triggers excessive return volatility.

While the literature shows that perks can affect firm values positively or negatively, we argue that firms with higher perks are more likely to be associated with a lower quality of financial reporting, which, in turn, can affect the informativeness of stock prices. Based on hand-collected data on perks from Chinese listed firms, we find that firms with lower perks are associated with higher informativeness of stock prices (or lower R-square). Moreover, the positive association between perks and R-square is shown to be weaker for firms with higher financial reporting quality through audit and earnings quality measures.

Asian initial public offerings (IPOs) require investors to pay subscription funds up-front upon submission of applications, and these funds are locked-up for 1–3 weeks without interest. Hence, the IPO process entails an explicit financing cost (opportunity cost) whether investors borrow funds or use their own funds to apply for IPO shares. The IPO subscription costs are not trivial, especially in a high interest rate environment or when an IPO is highly oversubscribed. These costs should be considered in any comparison of IPO returns across countries.

We extend Jin and Myers’s (2006) model to derive the relation between stock price crash risk and operating leverage (i.e., the fraction of fixed costs in total costs). The model predicts that (1) firms’ operating leverage decreases as stock price crash risk increases and (2) the negative effect of crash risk on operating leverage is more pronounced when firms are closer to the crash threshold or when managers face higher costs of stock price crashes. We empirically test the model predictions using a large sample of manufacturing firms in the US and find consistent results. Further analysis shows that higher levels of crash risk lead to a less sticky cost behavior. In addition, crash risk–driven operating deleveraging effectively reduces stock return volatility and enhances operating performance in subsequent years. Collectively, our findings reveal that crash-prone firms adopt a more flexible cost structure to delay stock price crashes and mitigate adverse outcomes.