We investigate the effect of information asymmetry on corporate tax avoidance. Using a difference-in-differences matching estimator to assess the effects of changes in analyst coverage caused by broker closures and mergers, we find that firms avoid tax more aggressively after a reduction in analyst coverage. We further find that this effect is mainly driven by firms with higher existing tax-planning capacity (e.g., tax-haven presence), smaller initial analyst coverage, and a smaller number of peer firms. Moreover, the effect is more pronounced in industries where reputation matters more and in firms subject to less monitoring from tax authorities.

We develop an estimation approach based on a modified expectation-maximization (EM) algorithm and a mixture of normal distributions associated with skill groups to assess performance in hedge funds. By allowing luck to affect both skilled and unskilled funds, we estimate the number of skill groups, the fraction of funds from each group, and the mean and variability of skill within each group. For each individual fund, we propose a performance measure combining the fund’s estimated alpha with the cross-sectional distribution of fund skill. In out-of-sample tests, an investment strategy using our performance measure outperforms those using estimated alpha and t -statistic.

We find that stock liquidity increases stock price crash risk. To identify the causal effect, we use the decimalization of stock trading as an exogenous shock to liquidity. This effect is increasing in a firm’s ownership by transient investors and nonblockholders. Liquid firms have a higher likelihood of future bad earnings news releases, which are accompanied by greater selling by transient investors, but not blockholders. Our results suggest that liquidity induces managers to withhold bad news, fearing that its disclosure will lead to selling by transient investors. Eventually, accumulated bad news is released all at once, causing a crash.