Relative performance evaluation (RPE) in chief executive officer (CEO) compensation can be used as a commitment device to pay CEOs for their revealed relative talent. We find evidence consistent with the talent-retention hypothesis, using two different approaches. First, we examine the RPE terms in compensation contracts and document features that are consistent with retention motives. Second, using a novel empirical specification for detecting RPE, we find RPE is less prevalent when CEO talent is less transferrable: Among specialist CEOs, founder CEOs, and retirement-age CEOs, as well as in industries and states where the market for CEO talent is more restrictive.

We hypothesize that corporate income taxes distort firms’ incentives to innovate by reducing their pledgeable income. Using a differences-in-differences methodology, we document that large corporate income tax cuts boost corporate innovation. We find a similar but opposite effect for tax increases. Most of the change in innovation occurs 2 or more years after the tax change, and there’s no effect before the tax change. Exploring the mechanisms, we show that tax cuts have a stronger impact on innovation for firms with weaker governance, greater financial constraints, fewer tangible assets, smaller patent stock, and a greater degree of tax avoidance.

We study the role of the contractual time horizon of chief executive officers (CEOs) for CEO turnover and corporate policies. Using hand-collected data on 3,954 fixed-term CEO contracts, we show that remaining time under contract predicts CEO turnover. When contracts are close to expiration, turnover is more likely and is more sensitive to performance. We also show a positive within-CEO relation between remaining time under contract and firm risk. Our results are similar across short and long contracts and are driven neither by firm or CEO survival, nor technological cycles. They are consistent with incentives to take long-term projects with interim volatility.

In this article, we survey the literature that studies fixed-income trading rules and outcomes, including Treasury securities, corporate and municipal bonds, and structured credit products. We compare and contrast the microstructure and regulation of fixed-income markets with equity markets. We highlight the nature of over-the-counter trading in the face of search costs and the associated slow evolution of electronically facilitated intermediation. We discuss the databases available to study fixed-income microstructure, as well as measures and determinants of trading costs, and the important roles dealer networks and limited transparency play. We also highlight unresolved issues.

Though short sellers on average succeed at identifying overvalued equity, firms often signal disagreement with short sellers by repurchasing stock when short interest increases. We investigate whether this disagreement reflects a myopic defense of inflated prices, or positive private information. These repurchases appear motivated by managers’ private information, not agency issues, even when managerial benefits to short-termism are enhanced or monitoring is weaker. Managers’ informational advantage relates to subsequent news, earnings, and risk, but is attenuated if activists target management or insiders sell. A trading strategy based on our findings earns 7.5% annually.

We distinguish between “good” and “bad” carry trades constructed from Group of Ten (G-10) currencies. The good trades exhibit higher Sharpe ratios and sometimes positive return skewness, in contrast to the bad trades, which have both substantially lower Sharpe ratios and highly negative return skewness. Surprisingly, good trades do not involve the most typical carry currencies like the Australian dollar and Japanese yen. The distinction between good and bad carry trades significantly alters our understanding of currency carry trade returns, and invalidates, for example, explanations invoking return skewness and crash risk.

We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.

In this article, we propose two asymmetry measures for stock returns. Unlike the popular skewness measure, our measures are based on the distribution function of the data rather than just the third central moment. We present empirical evidence that the greater upside asymmetries calculated using our new measures imply lower average returns in the cross section of stocks. In contrast, when using the skewness measure, the relationship between asymmetry and returns is inconclusive.

We provide a theoretical rationale for dealer objections to ex post transparency in over-the-counter markets. Disclosure of the terms of a transaction conveys information possessed by the dealer about the asset quality and reduces the dealer’s rents when she disposes of the inventory in a second transaction. We show that costly signaling in a transparent market benefits investors through lower spreads and higher volume. Dealers may also gain from transparency despite lower spreads when potential gains from trade are small or adverse selection is high, because in those circumstances higher volume offsets smaller spreads for dealer profits.

Based on intraday data for a large cross section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measures, or “good” and “bad” volatilities, associated with positive and negative high-frequency price increments, respectively. Sorting the individual stocks into portfolios based on their normalized good minus bad volatilities results in economically large and highly statistically significant differences in the subsequent portfolio returns. These differences remain significant after controlling for other firm characteristics and explanatory variables previously associated with the cross section of expected stock returns.

We examine whether political corruption impedes innovation. Using a comprehensive sample of U.S. firms, we find that corruption has a substantial, negative relation with the quantity and quality of innovation. These results are robust to using various fixed effects, proxies for corruption and innovation, and subsamples. To establish causality, we employ 2 instruments for corruption: local ethnic diversity and the corruption of the state a firm’s founder grew up in. Corruption appears to reduce innovation output both on average and for the most innovative firms. Overall, this evidence is consistent with the notion that corruption reduces social welfare by impeding innovation.

How does informed trading affect liquidity in limit order markets, where traders can choose between market orders (demanding liquidity) and limit orders (providing liquidity)? In a dynamic model, informed trading overall helps liquidity: A higher share of informed traders i) improves liquidity as proxied by the bid–ask spread and market resiliency, and ii) has no effect on the price impact of orders. The model generates other testable implications, and suggests new measures of informed trading.

We identify a positive causal effect of healthy working environments on corporate innovation, using the staggered passage of U.S. state-level laws that ban smoking in workplaces. We find a significant increase in patents and patent citations for firms headquartered in states that have adopted such laws relative to firms headquartered in states without such laws. The increase is more pronounced for firms in states with stronger enforcement of such laws and in states with weaker preexisting tobacco controls. We present suggestive evidence that smoke-free laws affect innovation by improving inventor health and productivity and by attracting more productive inventors.

Intermediation in private equity involves illiquid investments, professional investors, and high information asymmetry. We use this unique setting to empirically evaluate theoretical predictions regarding intermediation. Using placement agents has become nearly ubiquitous, but agents are associated with significantly lower abnormal returns in venture and real estate funds, consistent with investor capture and influence peddling. However, returns are higher for buyout funds employing a top-tier agent and for first-time real estate and venture funds employing an agent, and are less volatile for agent-affiliated funds, consistent with a certification role. Our results suggest heterogeneous motives for intermediation in the private equity industry.

We study the effects of market incompleteness on speculation, investor survival, and asset pricing moments when investors disagree about the likelihood of jumps and have recursive preferences. We consider two models. In a model with jumps in aggregate consumption, incompleteness barely matters because the consumption claim resembles an insurance product against jump risk and effectively reproduces approximate spanning. In a long-run risk model with jumps in the long-run growth rate, market incompleteness affects speculation and investor survival. Jump and diffusive risks are more balanced regarding their importance, and therefore the consumption claim cannot reproduce approximate spanning.

Between 2009 and 2013, the Fly on the Wall (FLY) leaked 58% of recommendation revisions with a median delay of 27 minutes relative to the IBES announcement time. We show that FLY improves price discovery, but leaked recommendations hamper brokers’ ability to offer price improvement on trades routed through them. Three major brokers sued FLY; using key court dates, we show significant wealth and real effects to the brokerage industry. Overall, the speed with which analyst recommendations are disseminated has led to more rapid price discovery at the expense of a decline in the scope of the sell-side research industry.

We develop a tractable dynamic model of an index option market maker with limited capital. We solve for the variance risk premium and option prices as a function of the asset dynamics and market maker option holdings and wealth. The market maker absorbs end users’ positive demand and requires a more negative variance risk premium when she incurs losses. We estimate the model using returns, options, and inventory and find that it performs well, especially during the financial crisis. The restrictions imposed by nested existing reduced-form stochastic-volatility models are strongly rejected in favor of the model with a market maker.

This paper investigates the relation between media coverage and offering yield spreads using a comprehensive dataset of 5,338 industrial bonds issued from 1990 to 2011. We find that media coverage is negatively associated with firms’ cost of debt. This association is robust to controlling for standard yield determinants, different model specifications, and endogeneity. We identify 4 economic channels through which media coverage influences the cost of debt: Information asymmetry, governance, liquidity, and default risk. Importantly, media coverage has an independent influence beyond the effects of these economic mechanisms and is not a proxy for other firm attributes.

We show how to conduct asymptotically valid tests of model comparison when the extent of model mispricing is gauged by the squared Sharpe ratio improvement measure. This is equivalent to ranking models on their maximum Sharpe ratios, effectively extending the Gibbons, Ross, and Shanken (1989) test to accommodate the comparison of nonnested models. Mimicking portfolios can be substituted for any nontraded model factors, and estimation error in the portfolio weights is taken into account in the statistical inference. A variant of the Fama and French (2018) 6-factor model, with a monthly updated version of the usual value spread, emerges as the dominant model.

In this paper we present empirical tests of an extended version of the capital asset pricing model (CAPM) that replaces the single-period horizon with a probability distribution over different horizons. Adopting a simple parameterization of the probability distribution of the length of the horizon, we estimate the parameters of the distribution as well as the parameters of the CAPM. We find that the extended model is not rejected for several different samples of common stocks, and for these samples it outperforms not only the standard CAPM but also the Fama–French (1993) 3-factor model. The probability distribution over horizon dates varies over time with the New York Stock Exchange (NYSE) turnover rate. We also find that returns satisfy the Euler equation of a representative financial institution that holds the market portfolio and has horizon probabilities estimated from 13F filings.