Announcements of mergers very often discuss the immediate impact of the deal on the acquirer’s earnings per share (EPS). We argue that the focus on EPS reflects the difficulty of evaluating and communicating deal synergy in mergers and acquisitions (M&A) practice and provide supporting evidence. We show that the acquirer’s EPS focus affects how deals are structured, the premium that is paid, and the types of deals that are done. EPS-driven M&A decisions are also associated with costly distortions in the acquirer’s financial and investment policies.

Retail order imbalance positively predicts returns, but on average retail investor trades lose money. Why? Order imbalance tests equal-weighted stocks, but retail purchases concentrate on attention-grabbing stocks that subsequently underperform. Long–short strategies based on extreme quintiles of retail order imbalance earn dismal annualized returns of −14.8% among stocks with heavy retail trading but earn 6.6% among other stocks. Our results reconcile the literatures on the performance of retail investors, the predictive content of retail order imbalance, and attention-induced trading and returns. Smaller retail trades concentrate more on attention-grabbing stocks and perform worse.

We show theoretically that the usual estimated investment strategies will not achieve the optimal Sharpe ratio when the dimensionality is high relative to sample size, and the $ 1/N $ rule is optimal in a 1-factor model with diversifiable risks as dimensionality increases, which explains why it is difficult to beat the $ 1/N $ rule in practice. We also explore conditions under which it can be beaten, and find that we can outperform it by combining it with the estimated rules when $ N $ is small, and by combining it with anomalies or machine learning portfolios, conditional on the profitability of the latter, when $ N $ is large.

We show that demand effects generated by institutional frictions can influence systematic return predictability patterns in stocks and mutual funds. Identification relies on a reform to the Morningstar rating system, which we show caused a structural break in style-level positive feedback trading by mutual funds. As a result, momentum-related factors in stocks, as well as performance persistence and the “dumb money effect” in mutual funds, experienced a sharp decline. Consistent with the proposed channel, return predictability declined right after the reform, was limited to the U.S. market, and was concentrated in factors and mutual funds most exposed to the mechanism.

Momentum profits depend mainly on the short leg and therefore on barriers to short sales. Our research indicates that the decline in momentum profitability in the past 2 decades is driven partly by a contemporaneous growth in stock options trading. Stock options offer an alternative to short selling, augmenting the stock lending market, and thereby contributing to improved pricing efficiency. The resulting reduction in barriers to short sales contributes to lower returns to momentum trading from the short leg. Our results persist after matching stocks with and without options based on different firm-level characteristics.

We propose a novel measure of the market return tail risk premium based on minimum-distance state price densities recovered from high-frequency data. The tail risk premium extracted from intra-day S&P 500 returns predicts the market equity and variance risk premiums and expected excess returns on a cross section of characteristics-sorted portfolios. Additionally, we describe the differential role of the quantity of tail risk, and of the tail premium, in shaping the future distribution of index returns. Our results are robust to controlling for established measures of variance and tail risk, and of risk premiums, in the predictive models.

Using detailed data on U.S. households’ locations, employment, and financial portfolios, we document that individuals employed in locally clustered industries are more likely to invest in risky assets. This pattern is strongest among individuals with high labor income, employed in skilled occupations, and with strong cognitive skills. Our overall evidence suggests the relation between industry clusters and investment decisions is best explained by clusters enhancing human capital among local industry workers, in turn amplifying their effective risk tolerance. Our findings highlight the important role of local labor market composition in generating household portfolio patterns within and across geographies.

Credit default swaps (CDSs) are a major financial innovation related to debt contracting. Because CDS markets facilitate bad news being incorporated into equity prices via cross-market information spillover, CDS availability may curb firms’ information hoarding. We find that CDS trading on a firm’s debt reduces the future stock price crash risk. This effect is stronger in active CDS markets, when the main lenders are CDS market dealers with securities trading subsidiaries, or when managers have more motivation to hoard information. Our findings suggest that debt market financial innovations curtail the negative equity market effects of firms withholding bad news.

We use a random forest model to classify firms’ financial constraints using only financial variables. Our methodology expands the range of classified firms compared to text-based measures while maintaining similar levels of informativeness. We construct two versions of our constraint measures, one using many firm characteristics and the other using a small set of more primitive characteristics. Using our measures, we find that institutional investors hold a lower percentage of shares in equity-focused constrained firms, while retail investors show a preference for them. Equity issuance and investment of constrained firms also increases during periods of high investor sentiment.

We examine the role of peer (e.g., Lipper manager indices) versus pure (e.g., S&P 500) benchmarks in fund manager compensation. We model their impact on manager incentives and then test those predictions using novel data. We find that 71% of managers are compensated based on peer benchmarks. Consistent with the model, peer-benchmarked fund managers exhibit higher effort generating higher gross performance and collect higher fee income. Analyzing advisors’ choice between benchmark types, we show that peer-benchmarking advisors cater to more sophisticated and performance-sensitive investors, and are more likely to sell through direct channels, consistent with investor heterogeneity and market segmentation.

Exploiting two quasi-natural experiments, we find that firms increase emissions of toxic pollution following decreases in analyst coverage. The effects are stronger for firms with low initial analyst coverage, poor corporate governance, and firms subject to less stringent monitoring by environmental regulators. Decreases in environmental-related questions raised in conference calls, an increased cost of monitoring to institutional shareholders, reductions in pollution abatement investment, and the weakening of internal governance related to environmental performance are channels through which reduced analyst coverage contributes to increases in firm pollution. Our study highlights the monitoring role analysts play in shaping corporate environmental policies.

We find that mortgage loans originated after the adoption of the inevitable disclosure doctrine (IDD; a mechanism discouraging loan officers’ labor mobility) have a lower default probability, a higher loan modification rate, and a lower foreclosure rate. These effects are unaccompanied by any reduction in loan supply and contribute to more stable housing prices. Using the adoption of the Uniform Trade Secrets Act as an alternative identification generates consistent results. Overall, our findings suggest that restricting loan officers’ labor mobility leads to better ex ante screening and ex post monitoring, improving the origination efficiency for U.S. residential mortgage loans.

This study investigates whether the management earnings forecasts of Republican and Democratic CEOs differ due to systematic differences in their information disclosure preferences. We find that Republican CEOs prefer a less asymmetric information environment than Democrat CEOs, and thus make more frequent, timelier, and more accurate disclosures than Democrat CEOs. Results using the propensity score matched sample and difference-in-differences analysis show that our results are unlikely to be driven by potential endogeneity. Our results are robust to controlling for various CEO characteristics and are stronger for firms with higher levels of institutional ownership and litigation risk.

We introduce a new approach to estimating long-term aggregate discount rates using the cross section of earnings and book values to explain current stock prices and extract expected market returns. The proposed discount rate measure is countercyclical. Shocks to it account for nearly half of historical market return variation; in contrast, shocks to other discount rate measures account for no more than 2%. It dominates other measures in explaining time-series variation in returns on duration-sorted portfolios and delivers out-of-sample predictability that exceeds that afforded by other expected return measures and predictive variables. It also performs well in international equity markets.

We examine the effects of implementing a U.S. approach to the enforcement of mandatory disclosure in China. Using a hand-collected sample of comment letters (CLs) issued by the Shanghai Stock Exchange over the period of 2013 to 2018, we show that stock price reactions to CL receipts and replies are negative and significant. Using textual analysis to match issues raised by regulators to targeted firms’ changes in disclosure, we show that these firms do address CL issues point by point, but do not experience significant improvements in their information environments. Our article highlights the importance of incentives rather than regulation/enforcement in reducing information asymmetry.

We propose a novel model-free approach to obtain the joint risk-neutral distribution among several assets that is consistent with options on these assets and their weighted index. We implement this approach for the nine industry sectors comprising the S&P 500 index and find that their option-implied dependence is highly asymmetric and time-varying. We then study two conditional correlations: when the market moves down or up. The risk premium is strongly negative for the down correlation but positive for the up correlation. Intuitively, investors dislike the loss of diversification when markets fall, but they actually prefer high correlation when markets rally.

During the first half of 2020, the difference in savings from mortgage refinancing between high- and low-income borrowers was 10 times higher than before. This was the result of two factors: high-income borrowers increased their refinancing activity more than otherwise comparable low-income borrowers and, conditional on refinancing, they captured slightly larger improvements in interest rates. Refinancing inequality increases with the severity of the COVID-19 pandemic and is characterized by an underrepresentation of low-income borrowers in the pool of applications. We estimate a difference of $5 billion in savings between the top income quintile and the rest of the market.

This article studies the effects of state minimum wage increase on information technology (IT) adoption at the establishment level in the United States. Our results show that treatment establishments on average allocate between $10,328 and $66,808 more per year to their IT budgets during the first 3 years after experiencing significant state minimum wage increases. Additional evidence shows that state minimum wage increases on average lead to an economically small decrease in employment. The estimated employment effect is larger for establishments that have more incentives to automate labor. Our results suggest that establishments adopt technology to countervail increased labor costs.

Banks’ information technology (IT) capabilities affect their ability to serve customers during the COVID-19 pandemic, which generates an unexpected and unprecedented shock that shifts banking services from in-person to digital. Amid mobility restrictions, banks with better IT experience larger reductions in physical branch visits and larger increases in website traffic, implying a larger shift to digital banking. Stronger IT banks are able to originate more Paycheck Protection Program loans to small business borrowers, especially in areas with more severe COVID-19 outbreaks, higher internet use, and higher bank competition. Those banks also attract more deposit flows and receive better mobile customer reviews during the pandemic.

The literature provides conflicting arguments and mixed results regarding whether capital markets punish managerial myopia. Using managers cutting research and development (R&D) investments to meet short-term earnings goals as a research setting, this study reveals that capital markets penalize managerial myopia, especially for firms with high investor sophistication. Moreover, the negative market reactions to managerial myopia are weaker for firms with overinvestment problems than for those without such problems. Overall, the results support the notion that security markets are not shortsighted. In further analysis, we document that compensation, especially earnings-based compensation, may cause managers to behave myopically. Our study contributes to the literature, reconciling previously mixed findings by capturing managers’ myopic behavior in a more targeted way and showing that markets punish myopic R&D cutting.