This paper examines management’s motives for rejecting takeover bids and the associated shareholder wealth effects. We develop measures of initial bid quality and find a significant negative correlation between the quality of a bid and rejection. The likelihood of higher follow-on offers decreases with bid quality and is greater when targets have classified boards and chief executive officers (CEOs) with significant personal wealth tied to the transaction. Target CEOs who fail to close high-quality offers experience a significant rate of forced turnover. Overall, the results support a price improvement motive for contested bids.

We explore the properties of equity mutual funds that experience a loss of assets after poor performance. We document that both inflows and outflows are less sensitive to performance, because performance-sensitive investors leave or decide not to invest after bad performance. Consistent with the idea that attrition measures the sorting of performance-sensitive investors, we find that attrition has less of an impact on the fund’s flow–performance sensitivity for institutional funds where there is less dispersion in investor performance sensitivity. Also, attrition has no effect on the flow–performance sensitivity when attrition arises after good performance or investors invest for nonperformance reasons.

We investigate whether incentives to join the Fortune 500 affect corporate decisions. Firms closer to the cutoff appear to take actions to join the list by engaging in more mergers and acquisitions activity, bidding for larger targets, and paying higher takeover premia. Further, the relation is stronger for firms with more-entrenched chief executive officers, and the stock market reaction to bids is worse when bidders are close to the Fortune 500’s cutoff. A 1994 methodological change by Fortune acts as an exogenous shock for identification. Our results suggest that firms try to increase revenues to join the Fortune 500 but that such actions adversely affect shareholders.

We present a simple 2-factor model that helps explain several capital asset pricing model (CAPM) anomalies (value premium, return reversal, equity duration, asset growth, and inventory growth). The model is consistent with Merton’s intertemporal CAPM (ICAPM) framework, and the key risk factor is the innovation on a short-term interest rate, the federal funds rate, or the T-bill rate. This model explains a large fraction of the dispersion in the average returns of the joint market anomalies. Moreover, the model compares favorably with alternative multifactor models widely used in the literature. Hence, short-term interest rates seem to be relevant for explaining several dimensions of cross-sectional equity risk premia.

The 2012 Dividend Tax Reform in China ties individual investors’ dividend tax rates to the length of their shareholding period. We find that firms facing a reduction (increase) in their individual investors’ dividend tax rates are more (less) likely to increase dividend payout. Such an effect is concentrated in firms where incentives of controlling shareholders and minority shareholders are aligned. Furthermore, investors respond to this tax law change by reducing trading activities before the cum-dividend day and successfully lower their dividend tax penalty. Overall, our evidence enhances the notion that individual investors’ tax profiles shape firms’ payout policies.

We provide novel evidence on gender differences in insider-trading behavior and the profitability of senior corporate executives. On average, both female and male executives make positive profits from insider trading. Males, however, earn significantly more than females in equivalent positions and also trade more than females. These gender differences disappear when we limit the sample to firms in which female trading is relatively high. Collectively, these results suggest that female executives have a disadvantage relative to males in access to inside information, even if they have equal formal status, and informal networks may play an important role in attenuating this disadvantage.

We find that firms headquartered in U.S. counties with higher levels of social capital incur lower bank loan spreads. This finding is robust to using organ donation as an alternative social capital measure and incremental to the effects of religiosity, corporate social responsibility, and tax avoidance. We identify the causal relation using companies with a social-capital-changing headquarters relocation. We also find that high-social-capital firms face loosened nonprice loan terms, incur lower at-issue bond spreads, and prefer public bonds over bank loans. We conclude that debt holders perceive social capital as providing environmental pressure that constrains opportunistic firm behaviors in debt contracting.

I model the decision of an informed early-stage venture capital (VC) investor that considers involving an uninformed VC or venture lending (VL) investor to finance the late stage. Early-stage VC investors that own high-quality value companies tend to signal their quality and they frequently turn to VL investors. Early-stage VC investors prefer VC if the proportion of high-quality companies in the population is high, if their companies have a high upside potential, if they can benefit from the value that late-stage VC investors add, or if uncertainty is high. I find empirical evidence consistent with these predictions.

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 examine whether internal funds matter for investment when the measurement error in q is addressed. By carefully employing methodologies that tackle the measurement error in q, we show that cash flow is a significant determinant of investment. We also find that an analyst-forecast-based q measure is not superior to a stock-market-based q measure. We further propose an approach that uses two alternative proxies of q as instruments for addressing measurement error. Our evidence indicates that instrumental-variables-type generalized method of moments estimators yield empirically well-specified models.

On Mar. 21, 2007, the U.S. Securities and Exchange Commission (SEC) passed Exchange Act Rule 12h-6 to make it easier for cross-listed firms to deregister from the U.S. market and escape its regulatory costs. Using difference-in-difference (DD) tests, we find that, on average, Rule 12h-6’s passage induced an increase in voting premium, a decline in equity raising, and a decline in cross-listing premium. These effects are observed for exchange-listed firms and for firms from countries with weak investor protection. We conclude that although cross-listed firms are still valued at a significant premium over non-cross-listed firms, the rule decreased the value of commitment to the U.S. regulatory system.

We solve for optimal consumption and portfolio choice in a life-cycle model with short-sales and borrowing constraints; undiversifiable labor income risk; and a predictable, time-varying, equity premium and show that the investor pursues aggressive market timing strategies. Importantly, in the presence of stock market predictability, the model suggests that the conventional financial advice of reducing stock market exposure as retirement approaches is correct on average, but ignoring changing market information can lead to substantial welfare losses. Therefore, enhanced target-date funds (ETDFs) that condition on expected equity premia increase welfare relative to target-date funds (TDFs). Out-of-sample analysis supports these conclusions.

I develop a new predictive approach using Bayesian model averaging to account for incomplete knowledge of the true model behind corporate default and bankruptcy filing. I find that uncertainty over the correct model is empirically large, with far fewer variables being significant predictors of default compared with conventional approaches. Only the ratio of total liabilities to total assets and the volatility of market returns are robust default predictors in the overall sample and individual industry groups. Model-averaged forecasts that aggregate information across models or allow for industry-specific effects substantially outperform individual models.

We consider a broad class of dynamic portfolio optimization problems that allow for complex models of return predictability, transaction costs, trading constraints, and risk considerations. Determining an optimal policy in this general setting is almost always intractable. We propose a class of linear rebalancing rules and describe an efficient computational procedure to optimize with this class. We illustrate this method in the context of portfolio execution and show that it achieves near optimal performance. We consider another numerical example involving dynamic trading with mean-variance preferences and demonstrate that our method can result in economically large benefits.

We compare two bootstrap methods for assessing mutual fund performance. The first produces narrow confidence intervals due to pooling over time, whereas the second produces wider confidence intervals because it preserves the cross correlation of fund returns. We then show that the average U.K. equity mutual fund manager is unable to deliver outperformance net of fees under either bootstrap. Gross of fees, 95% of fund managers on the basis of the first bootstrap and all fund managers on the basis of the second bootstrap fail to outperform the luck distribution of gross returns.