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.

This article proposes a novel way to estimate consumer switching costs and uses Lithuanian credit register data and two bank closures to provide this estimate for the loan market. I show that when a distressed bank’s closure forced firms to switch, they started borrowing at lower interest rates instantly and permanently and that this drop revealed the lower bound of firms’ ex ante switching costs. A healthy bank’s closure showed no such effect. The article’s findings suggest that distressed banks hold up and overcharge firms and that by closing and resolving such banks with good-bank/bad-bank separation regulators can improve firm financing.

Due to the government-driven mergers of large banks, many competing firms in Japan ended up borrowing from a common lender. Using firm-level data, we find that the capital investments of competing firms that share a common lender decrease by 15% of the mean. When a common lender can exercise its voice through its former employees serving as firms’ executive directors, investments fall significantly further. Competing firms that share a common lender increase markups and profitability ratios, suggesting that the lender induces strategic coordination among its borrowers to reduce their competitive pressures. Firms use saved resources from weaker competition for cash cushions.

Investment managers connected to plans sponsors are more likely to be hired than not-connected managers. The magnitude of the selection effect is comparable to that of prior performance. Ex post, connections do not result in higher post-hiring returns. Relationships are thus conducive to asset gathering by investment managers but do not generate commensurate pecuniary benefits for plan sponsors.

We show large flows of workers into the real estate agent (REA) occupation during the early 2000s from virtually all parts of the skill, wage, and education spectrums. We find those entering REA in Metropolitan Statistical Areas (MSAs) with house price bubbles end up in occupations paying significantly less in the long-run as compared to similar REA entrants in non-bubble areas. Even in 2017, when house prices and employment return to their pre-crisis levels, REA entrants in Bubble MSAs are in occupations earning about 6% less. These results point to lasting effects of labor allocation decisions in response to distorted price signals.

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.

I study whether the Dodd–Frank whistleblower program reduced informed trading by corporate insiders. To identify the effect, I partition firms based on the extent to which this program affected the likelihood of whistleblowing at each firm. I find a relative reduction in trading profits on purchases made by insiders at more affected firms after the program was initiated. I analyze insider sales in settings where they are more likely to be informed and find a reduction in the number of sales before negatively perceived events. The results suggest that whistleblower protections and rewards can effectively deter insider trading.

I propose a novel measure to identify family firms based on the number of family links between high-ranking coworkers. Leveraging this measure, I reexamine previous findings in the literature and derive four novel facts: i) Measures of stock ownership misclassify firms with a large family presence. ii) Family-run firms exhibit value stock characteristics, whereas founder-CEO firms display growth stock characteristics. iii) Family-run firms pay lower costs. iv) Family managers behave myopically. I conclude that failing to consider family links can lead to highly misleading results in the study of family firms.

Using data on nearly 20,000 restaurants in China during the COVID-19 outbreak, we find evidence that the government-sponsored rent reduction program reduced debt overhang problems. Rent reductions, which averaged 36,000 RMB per restaurant, increase the open rate of restaurants by 3.7%, revenue by 11,000 RMB, and the number of employees by 0.36. Larger restaurants with higher committed costs benefit more from the rent reduction. The stimulus has a positive spillover effect that boosts the revenue of restaurants in the immediate vicinity of subsidized restaurants. The treatment effect varies with organizational structure in a manner consistent with an information frictions hypothesis.

What are the implications of an aging population for financial stability? To examine this question, we exploit geographic variation in aging across U.S. counties. We establish that banks with higher exposure to aging counties increase loan-to-income ratios. Laxer lending standards lead to higher nonperforming loans during downturns, suggesting higher credit risk. Inspecting the mechanism shows that aging drives risk-taking through two contemporaneous channels: deposit inflows due to seniors’ propensity to save in deposits; and depressed local investment opportunities due to seniors’ lower credit demand. Banks thus look for riskier clients, especially in counties where they operate no branches.

This article uses the enactment of China’s 2007 Property Law (the Law), which reduces the risk of expropriation by local governments, as the setting to investigate the importance of property rights protection for private firm investment. Using propensity score matching and a difference-in-differences design, we find that firms facing weaker property rights protection prior to the Law significantly increase their investment and investment efficiency after the Law. Cross-sectional analyses document evidence consistent with a decrease in firms’ perceived expropriation risk as the main mechanism underlying the Law’s effect. Finally, we show that the Law improves local economic outcomes and employment.

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.

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.

Using a large sample of leveraged loans, we provide evidence that, despite having fewer creditor control rights, covenant-lite (Cov-Lite) loans have similar recovery rates and significantly lower spreads than loans with maintenance covenants. We find that the propensity to borrow Cov-Lite is related to various proxies for the reputational capital of a borrowing firm’s private equity sponsor. We construct a simple model to illustrate the relationship between reputational capital, covenants, and loan spreads in the leveraged loan market. Our model illustrates how reputational capital can substitute for covenants in mitigating agency costs of debt, leading to lower loan spreads for Cov-Lite loans.

This article presents an augmented deep factor model that generates latent factors for cross-sectional asset pricing. The conventional security sorting on firm characteristics for constructing long–short factor portfolio weights is nonlinear modeling, while factors are treated as inputs in linear models. We provide a structural deep-learning framework to generalize the complete mechanism for fitting cross-sectional returns by firm characteristics through generating risk factors (hidden layers). Our model has an economic-guided objective function that minimizes aggregated realized pricing errors. Empirical results on high-dimensional characteristics demonstrate robust asset pricing performance and strong investment improvements by identifying important raw characteristic sources.

We use New York City (NYC) taxi data to identify trips between mutual fund offices and local firm headquarters. NYC funds overweight the stocks of local firms they visit via taxi, and firm visits are associated with superior investment performance. Firm visits are elevated prior to earnings announcements, and mutual fund trades that are associated with firm taxi visits predict earnings surprises. The results are generally stronger when fund and firm executives share educational connections. Additional tests support the conclusion that funds’ local bias and investment performance are driven by portfolio managers’ efforts and ability to actively gather material information.

We investigate how men and women fare in the managerial labor market in the plausibly exogenous circumstance of their firms being acquired when most target-firm managers (about 90%) are displaced. These career disruptions result in a larger drop in rank and compensation for female managers, despite similar job search attributes. Gender differences are mitigated when hiring firms have more women in upper-echelon positions. Rich managerial experience and external board service also reduce gender-related differences. Overall, results point to a (implicit) “gender penalty” in terms of managerial job mobility, but also indicate contexts in which penalty is alleviated, and even reversed.

This article examines the pricing of a firm’s carbon risk in the corporate bond market. Contrary to the “carbon risk premium” hypothesis, bonds of more carbon-intensive firms earn significantly lower returns. This effect cannot be explained by a comprehensive list of bond characteristics and exposure to known risk factors. Investigating sources of the low carbon alpha, we find the underperformance of bonds issued by carbon-intensive firms cannot be fully explained by divestment from institutional investors. Instead, our evidence is most consistent with investor underreaction to the predictability of carbon intensity for firm cash-flow news, creditworthiness, and environmental incidents.

The cross section of options holds great promise for identifying return distributions and risk premia, but estimating dynamic option valuation models with latent state variables is challenging when using large option panels. We propose a particle Markov Chain Monte Carlo framework with a novel filtering approach and illustrate our method by estimating index option pricing models. Estimates of variance risk premiums, variance mean reversion, and higher moments differ from the literature. We show that these differences are due to the composition of the option sample. Restricting the option sample’s maturity dimension has the strongest impact on parameter inference and option fit in these models.

We develop 50 indices of state-level economic policy uncertainty (SEPU) based on newspaper coverage frequency using 204 million newspaper articles from Mar. 1984 to Dec. 2019. We assess the validity of our measures. Our SEPU indices vary counter-cyclically with respect to state-specific economic conditions, rise before close gubernatorial elections, and exhibit a large cross-sectional variation. We demonstrate that SEPU indices are associated with the cross-sectional variation in state-level GDP, employment, income as well as industry investment decisions. Our findings highlight the importance of economic policy uncertainty at the state level in addition to the nationwide level.