Knowledge that Transforms

This article argues that corporate financial frictions can have an adverse effect on employee mental health, an important determinant of employee productivity. To identify the causal effects of financial frictions, we exploit variation in firms’ need to refinance their long-term debt in 2008, a period when refinancing became more difficult due to the credit crunch. Using administrative microdata, we find that antidepressant use grows significantly more among employees of firms in higher need of debt refinancing. Much of this effect occurs at employees keeping their jobs, pointing to decreased perceptions of job security as a transmission channel.

We study household credit responses to Hurricane Harvey using new, geographically granular data on credit cards, mortgages, and flooding. Estimates from a differences-in-differences design that exploits the flooding gradient show that affected households only borrow at low-interest rates, often using promotional (zero interest) cards and that they quickly pay down balances. We also document that take-up of forbearance (borrowing by missing mortgage payments without penalty) increases with flooding. These results are attenuated in floodplains, particularly in structures subject by code to physical hardening. Our results indicate that credit acts as a substitute for the lack of physical hardening.

In this article, we show that firms can become conservative in innovation when their directors face job insecurity. We find that after the staggered enactment of majority voting legislation that strengthens shareholders’ power in director elections, firms produce fewer patents, particularly exploratory patents, and fewer forward citations. This effect is stronger for directors facing higher dismissal costs or threats and for firms with greater needs for board expertise and is mitigated by institutional investors’ expertise in innovation. Overall, our results suggest that heightened job insecurity induces director myopia, which leads to a reduction in investment in risky, long-term innovation projects.

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.

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 demonstrate the benefits of merging traditional hypothesis-driven research with new methods from machine learning that enable high-dimensional inference. Because the literature on post-earnings announcement drift (PEAD) is characterized by a “zoo” of explanations, limited academic consensus on model design, and reliance on massive data, it will serve as a leading example to demonstrate the challenges of high-dimensional analysis. We identify a small set of variables associated with momentum, liquidity, and limited arbitrage that explain PEAD directly and consistently, and the framework can be applied broadly in finance.

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.

A eurozone exit or breakup exposes bondholders to currency redenomination risk. I quantify redenomination risk since the sovereign debt crisis: It contributes substantially to credit spreads around changes in government in France and Italy. Bond prices suggest that markets have priced a potential Italian exit as isolated, and a French one as a breakup. Unlike conventional default risk, redenomination risk can be negative depending on the strength of the national “shadow” currency. Countries with strong shadow currencies earn breakup-insurance premia from the eurozone analog of “exorbitant privilege.” Yield effects are quantitatively large for implied exit probabilities as low as 1%.

Using the 2016 U.S. presidential election result as a shock to the expectations about the future regulatory environment, I find that most regulated firms earned approximately 4% higher cumulative abnormal stock returns than least regulated firms during the first 10 trading days after the election. Exploring economic mechanisms, I find evidence consistent with the explanation that more regulations disproportionately harm high-growth firms and allow incumbent firms to extract rents through lower competition and political favoritism. Stock returns are also followed by a shift in firm fundamentals over 3 years after 2016, consistent with the economic mechanisms.

We study the valuation of collateral by comparing spreads on loans by the same bank, to the same borrower, at the same origination date, but backed by different types of collateral. Pledging collateral reduces borrowing costs by 23 BPS on average. The effect varies across different types of collateral, with marketable securities being most valuable, and real estate and accounts receivables and inventory being more valuable than fixed assets and a blanket lien. Further, the rate reduction from pledging collateral is sensitive to the value of the underlying collateral, and collateral tends to be more valuable for smaller and private firms and for loans with longer maturity.