We summarize and synthesize the results of the articles in this symposium issue on research in financial economics related to the COVID-19 pandemic. We argue that the articles, taken together, present evidence that the pandemic resulted in a distributional shock to capital allocation. The underlying mechanisms include accelerating technological shifts, government stimulus programs, and heterogeneous responses of investors and firms. We augment these articles with evidence on the heterogeneous effects of the pandemic on profitability, payout, investment, employment, and productivity across sectors.

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.

We test how market overvaluation affects corporate innovation. Estimated stock overvaluation is strongly associated with measures of innovative inventiveness (novelty, originality, and scope), as well as research and development (R&D) and innovative output (patent and citation counts). Misvaluation affects R&D more via a nonequity channel than via equity issuance. The sensitivity of innovative inventiveness to misvaluation increases with share turnover and overvaluation. The frequency of exceptionally high innovative inputs/outputs increases with overvaluation. This evidence suggests that market overvaluation may generate social value by increasing innovative output and encouraging firms to engage in “moon shots.”

Hundreds of equity market intelligence financial technology firms (FinTechs) have formed in the last decade. We assemble novel data to describe their capabilities, users, and consequences. Our data suggest that these FinTechs i) aggregate many data sources, including nontraditional ones (e.g., Twitter, blogs), and synthesize such data using artificial intelligence to make investment recommendations, and ii) change Internet users’ information discovery by serving as substitutes for traditional information providers. We evaluate some nontraditional data and find evidence suggesting that such data contain valuable information or “crowd wisdom” that links to informational efficiency. Overall, our findings are consistent with this innovation benefiting investors and markets.

We study whether firms spread out debt-maturity dates, which we call granularity of corporate debt. In our model, firms that are unable to roll over expiring debt need to liquidate assets. If multiple small asset sales are less inefficient than a single large one, it can be optimal to diversify debt rollovers across time. Using a large sample of corporate bond issuers during the 1991–2012 period, we establish novel stylized facts and evidence consistent with our model’s predictions. There is substantial heterogeneity (i.e., firms have both concentrated and dispersed debt structures). Debt maturities are more dispersed for larger and more mature firms and for firms with better investment opportunities, higher leverage, and lower profitability. During the recent financial crisis, firms with valuable investment opportunities implemented more dispersed maturity structures. Finally, firms manage granularity actively and adjust toward target levels.

We develop a method for defining groups of peer firms on the basis of joint analyst coverage. Besides industry boundaries, analysts’ coverage choices reflect other aspects of firm relatedness such as business model. We find that the analyst-based method produces substantially more homogeneous groups of firms compared to common industry classifications, and has a number of other desirable properties. The paper has two broader implications. First, it demonstrates the advantages of a self-organizing approach to classification, as opposed to a hierarchical system. Second, it illustrates a new positive information production externality generated by the institution of security market analysis.

The literature examining analyst activity assumes that access to management is valued by analysts and their employers. We propose a readily observable measure of access: How often an analyst is invited to be among the first to ask questions in the Q&A session of an earnings conference call. These “early participants” are more successful in the labor market than peers from the same brokerage when their brokerages close. Our results show that access is valued by both sell-side and buy-side employers and reflects connectivity to management as well as analyst skill dimensions not captured in traditional measures of performance.

Firms can become less innovative following a sudden cash “inflow.” Specifically, multinational firms that were eligible to repatriate (and indeed repatriated) cash to the United States under the American Jobs Creation Act (AJCA) generate less valuable patents than otherwise similar firms. They also explore more. This effect only exists among firms in less competitive industries, firms with lower institutional ownership (IO), and firms with overconfident chief executive officers (CEOs); this effect is mainly driven by the reduction in the value of U.S.-originated patents. Our evidence suggests that, without appropriate governance, a cash windfall may lead managers to engage in riskier innovation strategy, which can destroy value.

We analyze how employee compensation contracts of target firms affect merger terms and outcomes. Using unique data from merger agreements, we document that in 80.0% of all merger and acquisition (M&A) deals, at least some of the target’s employee stock options (ESOs) are canceled by the acquirer and not replaced by new equity-based grants. Contract modifications reduce the value of ESOs by 38.4% in the average M&A deal. Further, the combined merger returns are larger when employees experience greater losses. Overall, our results indicate that the benefits of reducing the number of ESOs outweigh the potential negative effects on firm value.

We analyze lending by traditional as well as fintech lenders during COVID-19. Comparing samples of fintech and bank loan records across the outbreak, we find that fintech companies are more likely to expand credit access to new and financially constrained borrowers after the start of the pandemic. However, this increased credit provision may not be sustainable; the delinquency rate of fintech loans triples after the outbreak, but there is no significant change in the delinquency of bank loans. Borrowers holding both loan types prioritize the payment of bank loans. These results shed light on the benefits provided by shadow banking in a crisis and hint at the potential fragility of such institutions when delinquency rates spike.

Cross-firm predictability among economically linked firms can arise when both firms exhibit their own momentum and their returns are contemporaneously correlated. We show that cross-firm predictability can last up to 10 years, which is hard to reconcile with an interpretation of slow information diffusion. However, it is consistent with the economically linked firms’ commonality in momentum. The contribution of each source can be found by decomposing leaders’ returns into the predictable (momentum) and news components. Sorting on each, we find that both sources contribute almost equally to 1-month predictability, whereas commonality in momentum is solely responsible for longer-horizon cross-firm predictability.

Fiscal deficits represent an important variable for banks’ aggregate credit risk, revealing governments’ ability to curb banks’ losses in bad states, either with direct cash infusions or with macroeconomic stabilization policies. Deteriorating deficits are associated with increasing financial distress of the banking sector and higher levels of loan-loss provisions. The effect is more pronounced for banks with a strong aversion to underprovisioning and is robust to a battery of tests and to the identification of fiscal shocks using military-spending data. This association represents an additional source of negative comovement between provisions and economic conditions, with implications for financial stability.

Using establishment-level data, we examine the impact of the Indian government’s employment guarantee program on labor and firm behavior. We exploit the staggered implementation of the program for identification and find that the program led to a 10% reduction in the permanent workforce in firms. Firms responded to the adverse labor-supply shock by resorting to increased mechanization. This significantly increased the firms’ cost of production, leading to a decline in net profits and productivity. These effects manifested primarily in firms paying low wages, firms having low labor productivity and greater sales volatility, and firms located in states with pro-employer labor regulations.

We study changes in independent director behavior and labor-market outcomes after the experience of a forced Chief Executive Officer (CEO) turnover. We find that independent directors are more willing to fire CEOs of underperforming firms, hire outside CEOs after a firing, and encourage better board-meeting attendance by fellow directors. We also find that the shareholders of poorly performing firms react positively when experienced directors join the board. It does come with a small cost for directors, in terms of additional directorships, although the cost is not as great as that for directors who do not fire the CEO of a poorly performing firm.

We examine the causal effect of stakeholder orientation on firms’ cost of debt. Our test exploits the staggered state-level adoption of constituency statutes, which allows directors to consider stakeholders’ interests when making business decisions. We find a significant drop in loan spreads for firms incorporated in states that adopted such statutes relative to firms incorporated elsewhere. We further show that constituency statutes reduce the cost of debt through the channels of mitigating conflicts of interest between residual and fixed claimants and between holders of liquid claims and holders of illiquid claims, limiting legal liability and lowering takeover threats.

How does greater public disclosure of arbitrage activity and informed trading affect price efficiency? To answer this, we exploit rule amendments in U.S. securities markets, which impose a higher frequency of public disclosure of short positions. Higher public disclosure can hurt the production of information and deteriorate efficiency, or it can be beneficial by mitigating the limits to arbitrage and diffusing arbitrageurs’ information faster. With more frequent disclosure, information encapsulated within short interest is incorporated into prices faster, improving price efficiency. We find important reductions in short sellers’ horizon risk and increases in short sales with the rule amendments.

I document wage convergence in conglomerates using detailed plant-level data: Workers in low-wage industries collect higher-than-industry wages when the diversified firm also operates in high-wage industries. I confirm this effect by exploiting the implementation of the North American Free Trade Agreement (NAFTA) and changes in minimum wages at the state level as sources of exogenous increases in wages in some plants. I then track the evolution of wages of the remaining workers of the firm, relative to workers of unaffiliated plants. Plants where workers collect higher-than-industry wages operate with higher capital intensity, suggesting that internal labor markets may affect investment decisions in internal capital markets.

We show that the prices of risk for factors that are nonlinear in the market return can be obtained using index option prices. The price of coskewness risk corresponds to the market variance risk premium, and the price of cokurtosis risk corresponds to the market skewness risk premium. Option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An analysis of factor models with coskewness risk indicates that the new estimates of the price of risk improve the models’ performance compared with regression-based estimates.

This article studies the impact of retail investors on stock liquidity during the COVID-19 pandemic lockdown in spring 2020. Retail trading exhibits a sharp increase, especially among stocks with high COVID-19–related media coverage. Retail trading attenuated the rise in illiquidity by roughly 40% but less so for high-media-attention stocks. Causality is addressed using the staggered implementation of the stay-at-home advisory across U.S. states. The results highlight that ample free time and access to financial markets facilitated by fintech innovations to trading platforms are significant determinants of retail-investor stock market participation.

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use an exchange colocation service that increases AT as an exogenous instrument to draw causal inferences about AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.