Knowledge that Transforms

The 4 equity market factors from Fama and French (1993) and Carhart (1997) are pervasive in academia and practice. However, not much is known about their joint distribution and dynamics. We find striking evidence of asymmetric tail dependence across the factors. While the linear factor correlations are small and even negative, the extreme correlations are large and positive, so that the linear correlations drastically overstate the benefits of diversification across the factors. We model the nonlinear factor dependence dynamics and explore their economic importance in a portfolio allocation experiment showing that significant economic value is earned when acknowledging nonlinear dependence.

This study examines board monitoring when a credible chief executive officer (CEO) replacement is on the board. Inside directors whose talents are in greater demand externally, as reflected by their holding outside directorships, are more likely to become CEOs, and their presence is associated with greater forced CEO turnover sensitivity to accounting performance and CEO compensation sensitivity to stock performance. These results reveal that certain insiders strengthen board monitoring by serving as a readily available CEO replacement and contradict the presumption that all insiders are under CEO control. Furthermore, the results persist when accounting for the endogenous firm selection of talented inside directors.

Using unique daily fund-manager trade data, we examine the role of institutional trading in influencing firm performance. We show that short-horizon informed trading by multiple institutional investors effectively disciplines corporate management. Our focus is on short-term “swing” trades, sequences with three phases (e.g., buy-sell-buy). We find swing trades increase stock price informativeness, are profitable after costs, and improve market efficiency. This increase in stock price informativeness is associated with subsequent firm outperformance. Trades are most beneficial with optimal stock holdings that reflect the information acquisition incentives of investors as well as liquidity costs.

We characterize the relation between asset structure and capital structure by exploiting variation in the salability of corporate assets. To establish this link, we distinguish across different assets in firms’ balance sheets (machinery, land, and buildings) and use an instrumental approach that incorporates market conditions for those assets. We also use a natural experiment driving differential increases in the supply of real estate assets across the United States: The Defense Base Closure and Realignment Act of 1990. Consistent with a supply-side view of capital structure, we find that asset redeployability is a main driver of leverage when credit frictions are high.

The trading of securities on multiple markets raises the question of each market’s share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions, thereby resolving the main drawback of the widely used Hasbrouck (1995) methodology, which merely provides upper and lower bounds of a market’s information share. We show how tail dependence of price changes, which may emerge as a result of differences in market design, can be exploited to estimate unique information shares. Two empiricalapplications illustrate the practical use of the new methodology.

This paper provides a new explanation for why closed-end bond funds coexist along with otherwise identical open-end bond funds. Closed-end bond funds offer investors the opportunity to leverage their fixed income investment at very low borrowing rates and are attractive to investors for this reason. We find that differences in leverage are reflected in the discount on closed-end bond funds in a manner consistent with the advantage of leverage.

We compare investment policies across public and private firms in different institutional settings. Using a large cross-country data set, we find that public listed firms are better positioned to take advantage of growth opportunities than private firms. Specifically, public listed firms exhibit higher investment sensitivity to growth opportunities than private firms. This differential, however, only exists in countries with well-developed stock markets. Furthermore, the relative advantage public firms have at allocating capital depends on the degree of agency costs and reliance on external equity.

This paper develops a unified approach to comprehensively analyze individual hedge fund return predictability, both in and out of sample. In sample, we find that variation in hedge fund performance across changing market conditions is widespread and economically significant. The predictability pattern is consistent with economic rationale, and largely reflects differences in key hedge fund characteristics, such as leverage or capacity constraints. Out of sample, we show that a simple strategy that combines the funds’ return forecasts obtained from individual predictors delivers superior performance. We exploit this simplicity to highlight the drivers of this performance, and find that in- and out-of-sample predictability are closely related.

The paper explains why firms with high dispersion of analyst forecasts earn low future returns. These firms beat the capital asset pricing model in periods of increasing aggregate volatility and thereby provide a hedge against aggregate volatility risk. The aggregate volatility risk factor can explain the abnormal return differential between high- and low-disagreement firms. This return differential is higher for firms with abundant real options, and this fact can be explained by aggregate volatility risk. Aggregate volatility risk can also explain why the link between analyst disagreement and future returns is stronger for firms with high short-sale constraints.

Little evidence exists on whether boards help managers make better decisions. We provide evidence that strong and independent boards help overconfident chief executive officers (CEOs) avoid honest mistakes when they seek to acquire other companies. In addition, we find that once-overconfident CEOs make better acquisition decisions after they experience personal stock trading losses, providing evidence that a manager’s recent personal experience, and not just educational and early career experience, influences firm investment policy. Finally, we develop and validate a new CEO overconfidence measure that is easily constructed from machine-readable insider trading data, unlike previously used measures.