We estimate an ex ante probability of extreme negative returns (crashes) of individual stocks as a measure of potential overpricing and find that stocks with a high probability of crashes earn abnormally low returns. Stocks with high crash probability are overpriced regardless of the level of institutional ownership or variations in investor sentiment, and moreover, they exhibit increasing institutional demand until their prices reach the peak of overvaluation. We also find that institutional investors who overweight high crash probability stocks outperform the others, indicating that they have skill in timing bubbles and crashes of individual stocks. Our findings imply that sophisticated investors may not always trade against mispricing but time the correction of overpricing, and suggest that the crash effect we find could arise at least partially from rational speculative bubbles, not entirely from sentiment-driven overpricing.

This study investigates the impact of human capital (HC) quality on stock returns. We propose a measure of the quality of HC embedded in firms’ organization capital and show that firms with high-quality HC earn higher future stock returns than firms with low-quality HC, which is not attributable to prevalent risk factors or labor-related factors. The organization capital-to-assets ratio, capturing the relative quantity of organization capital, has significant but limited explanatory power for the return predictability of HC quality. We also confirm the adverse effects of increased HC costs on firm value. These findings are consistent with the argument that firms with higher HC quality have greater exposure to technology frontier shocks due to the risk of key talents leaving.

Recent evidence on state-dependent variations in market liquidity suggests strong variations in the illiquidity premium across economic states. Adopting a two-state Markov switching model, we find that, while illiquid stocks are affected more by economic conditions than liquid ones are during recessions, the differences in expected returns are relatively small during expansions. Therefore, the expected illiquidity premium displays strong state-dependent variations that are countercyclical. We show that the state of a high illiquidity premium is closely associated with periods of real economic recessions, market declines, and high volatility, which coincides with major events of liquidity dry-up and high liquidity commonality.

This study investigates the effects of short sale restrictions by extending the model of Dridi and Germain (2004) and infers informed traders’ strategies and the relation between order imbalance and price thereunder. The results are generally in line with the empirical evidence documented in the literature and are summarized as follows: First, seller-initiated trading incurs a greater price reaction. Second, short sale restrictions shift the skewness of asset returns. Third, the restrictions can stimulate investors to acquire information or increase each individual trader's order flow under the bullish and neutral signals as well as the bearish signal, which is yet to be explored empirically.

We develop a conditional version of the consumption capital asset pricing model (CCAPM) using the conditioning variable from the cointegrating relation among macroeconomic variables (dividend yield, term spread, default spread, and short-term interest rate). Our conditioning variable has a strong power to predict market excess returns in the presence of competing predictive variables. In addition, our conditional CCAPM performs approximately as well as Fama and French’s (1993) three-factor model in explaining the cross-section of the Fama and French 25 size and book-to-market sorted portfolios. Our specification shows that value stocks are riskier than growth stocks in bad times, supporting the risk-based story.