The U.S. Consumer Financial Protection Bureau has released a database of consumer complaints about banks’ financial products to the public since 2013. We find a greater reduction in mortgage applications to banks that receive more mortgage complaints in local markets after the disclosures. The effect is stronger in areas with more sophisticated consumers and higher credit competition, and for banks receiving more severe complaints. The number of monthly mortgage complaints per bank exhibits faster mean reversion after the publication of the database. These findings suggest that the public disclosure of mortgage complaints enhances product market discipline and consumer financial protection.

Using a novel data set of over 3,500 public and private firms, we construct the network of executive and director connections prior to the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates. Consistent with a working capital channel, the results are strongest for small, private, cash-poor firms, and firms located in counties with high bank suspension rates. Moreover, connections to cash-rich firms that increase accounts receivable matter the most. Our results suggest that network connections can play a stabilizing role during a financial crisis by easing the flow of capital to constrained firms.

We study how derivatives (with nonlinear payoffs) affect the underlying asset’s liquidity. In a rational expectations equilibrium, informed investors expect low conditional volatility and sell derivatives to the others. These derivative trades affect different investors’ utility differently, possibly amplifying liquidity risk. As investors delta hedge their derivative positions, price impact in the underlying drops, suggesting improved liquidity, because informed trading is diluted. In contrast, effects on price reversal are ambiguous, depending on investors’ relative delta hedging sensitivity (i.e., the gamma of the derivatives). The model cautions of potential disconnections between illiquidity measures and liquidity risk premium due to derivatives trading.

We study the drift and cyclical components in U.S. Treasury bonds. We find that bond yields are drifting because they reflect the drift in monetary policy rates. Empirically, modeling the monetary policy drift using demographics and productivity trends, plus long-term inflation expectations, leads to cyclical deviations of bond prices from their drift that predict bond returns in- and out-of-sample. These bond cycles can be interpreted as term premia or/and temporary deviations from rational expectations in a behavioral framework. Through the lens of our model, we detect a significant role of the latter in determining the cyclical properties of yields with short maturities.

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.

This article studies the relationship between credit provision and stock trading behavior. We collect every stock transaction of the three major British companies during the 1720 South Sea Bubble and link stock trading to margin loan positions with the Bank of England. We give insights in the selection of traders into the loan facility by comparing the trading behavior and realized returns of borrowers to other traders. We find that loan holders are more likely to buy following high returns and document strong underperformance of borrowers.

We view innovation investments as real options and explore the implications of risk (volatility) as well as a newly defined outcome independent measure of ambiguity (Knightian uncertainty) for innovation decisions. The empirical analysis uses stock returns to compute an implementable measure of ambiguity. We also control for risk and other determinants of innovation. We find a consistently significant negative effect of ambiguity on R&D, patents, and citations, as predicted. The effect of risk on R&D is positive and significant, but the corresponding effect on patents and citations is negative and significant. Ambiguity matters more for high-tech firms, consistent with intuition.

We explore the effects of online customer ratings on financial policy. Using a large sample of Parisian restaurants, we find a positive and economically significant relationship between customer ratings and restaurant debt. We use the locally exogenous variations in customer ratings resulting from the rounding of scores in regression discontinuity tests to establish causality. Favorable online ratings reduce cash flow risk and increase resilience to demand shocks. Consistent with the view that good online ratings increase the debt capacity of restaurants and their growth opportunities, restaurants with good ratings use their extra debt to invest in tangible assets.

This article studies how the rise of financial technology (Fintech) lending affects credit access, interest rates, and social welfare. We consider a lending competition model with two incumbent banks and a Fintech lender, which use different information and technologies to assess borrower creditworthiness. We show that Fintech lending could negatively affect high-quality borrowers’ access to credit when the Fintech lender’s screening accuracy is superior to that of the banks. Furthermore, Fintech lending may worsen the allocative efficiency of credit and reduce social welfare under some conditions. Analytical and numerical results suggest that Fintech lending mostly reduces the expected interest rates.

We develop a dynamic model of corporate investment and financing, in which shocks to the value of collateralizable assets generate variation in firms’ debt capacity. We show that the degree of similarity among firms’ financial flexibility forecasts cross-sectional variation in return correlation. We test the implications of the model with firm-level data in two empirical analyses using i) an instrumental variable approach based on shocks to the value of collateralizable corporate assets and ii) the outbreak of the COVID-19 crisis as an event study. We find that firms in the same percentile of the cross-sectional distribution of financial flexibility have 62% higher correlation in stock-return residuals than firms 50 percentiles apart.

I show that cash distributions through cash mergers, dividend payments, and stock buybacks are, in principle, similar to investor fund flows in generating demand for investable assets. Abnormal returns on certain assets can be forecasted because delegated investors predictably reinvest cash returns toward certain holdings. Novel measures of stock-level demand constructed using proportional reinvestments by mutual funds predict abnormal returns and issuances in noncash-paying stocks. These results highlight an alternative and substantial source of price fluctuations in the cross section of equities.

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 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.

We study how U.S. manufacturing firms’ investment responds to tariff reductions in supplier industries. Our estimates, based on tariff reductions following multinational trade agreements, suggest that a hypothetical 10% reduction of all upstream tariffs would increase downstream investment by 4% to 6%. This estimate is not explained by decreasing uncertainty and stems from tariff reductions for homogeneous and low-R&D inputs, consistent with the investment response resulting from cost reductions rather than superior foreign technology embodied in imported inputs. Evidence from an instrumental variable estimation using the sudden increase in Chinese import penetration suggests that import competition also increases downstream investment.

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.

We introduce a novel application of machine learning to compare pooling and servicing agreements (PSAs) that govern commercial mortgage-backed securities. In contrast to the view that the PSA is largely boilerplate text, we document substantial variation across PSAs, both within- and across-underwriters and over time. A part of this variation is driven by differences in loan collateral across deals. Additionally, we find that differences in PSAs are correlated with ex post loan and bond performance. Collectively, our analysis suggests the importance of examining the entire governing document, rather than specific components, when analyzing complex financial securities.

We show that merger announcement returns account for virtually all of the measured size premium. An empirical proxy for ex ante takeover exposure positively and robustly relates to cross-sectional expected returns. The relation between size and expected returns becomes positive or insignificant, rather than negative, conditional on this takeover characteristic. Asset pricing models that include a factor based on the takeover characteristic outperform otherwise similar models that include the conventional size factor. We conclude that the takeover factor should replace the conventional size factor in benchmark asset pricing models.

I show that an alignment in partisan affiliation, between a firm’s management and the president, is associated with higher levels of investment. Using insider trading data, I find that managers become more optimistic about their companies’ prospects when their preferred party is in power. This optimism-driven increase in investment is amplified by herding and associated with both lower profitability and stock returns. Overall, managers’ political beliefs produce heterogeneous expectations about future cash flows and distort investment decisions.

I show that hedge funds react to unrealized losses on their passive positions by engaging with the management. The hedge fund managers’ psychological response is consistent with cognitive dissonance: They blame the firms’ management and switch to activism. The loss, which is hedge fund-investment specific, is distinct from economic factors such as the firm’s industry-adjusted performance. Loss-driven activism is more likely to be unfocused on specific issues and results in worse firm performance. This study shows that an overlooked consequence of unrealized losses is to trigger an active engagement with the firm.

By employing a dynamic model with two limit order books, we show that fragmentation is associated with reduced competition among liquidity suppliers and lower picking-off risk of limit orders. Due to these countervailing channels, the impact of fragmentation on liquidity and welfare differs with asset volatility: When volatility is high (low), liquidity and aggregate welfare in a fragmented market are higher (lower) than in a single market. However, fragmentation always shifts welfare away from agents with exogenous trading motives and toward intermediaries. We empirically corroborate our model’s predictions about liquidity. Our model reconciles the mixed results in the empirical literature.