Knowledge that Transforms

I ask whether machine learning (ML) algorithms improve the efficiency in lending without compromising on equity in a credit environment where soft information dominates. I obtain loan application-level data from an Indian bank. To overcome the problem of the selective labels, I exploit the incentive-driven within officer difference in leniency within a calendar month. I find that the ML algorithm can lend 60% more at loan officers’ delinquency rate or achieve a 33% lower delinquency rate at loan officers’ approval rate. The efficiency is maintained even when the algorithm is explicitly prevented from discriminating against disadvantaged social classes.

We investigate the new reality of exchange-traded funds (ETFs). We show that most ETFs are active investments in form (designed to generate alpha) or function (serve as building blocks of active portfolios). We define a new activeness index to capture these dimensions, finding that the cross-section of ETFs is now increasingly characterized by highly active investment vehicles. Active-in-form ETFs have positive flow-performance sensitivity, charge the highest fees among ETFs, and have high within-portfolio turnover. Active-in-function ETFs have more concentrated holdings, less within-portfolio turnover, but higher turnover in the secondary market. We show how more active ETFs are gaining market share over less active ETFs, leading to competitive fee pressure both within the ETF space and across the investment management industry. We suggest that the growing activeness of ETFs may assuage concerns about ETFs harming price discovery.

Using merger announcements and applying methods from computational linguistics we find strong evidence that stock prices underreact to information in financial media. A one standard deviation increase in the media-implied probability of merger completion increases the subsequent 12-day return of a long-short merger strategy by 1.2 percentage points. Filtering out the 28% of announced deals with the lowest media-implied completion probability increases the annualized alpha from merger arbitrage by 9.3 percentage points. Our results are particularly pronounced when high-yield spreads are large and on days when only few merger deals are announced.

We use the text of financial stability reports (FSRs) published by central banks to analyze the relation between the sentiment they convey and the financial cycle. We construct a dictionary tailored specifically to a financial stability context, which classifies words as positive or negative based on the sentiment they convey in FSRs. With this dictionary, we construct financial stability sentiment (FSS) indexes for thirty countries between 2005 and 2017. We find that central banks’ financial stability communications are mostly driven by developments in the banking sector. Moreover, the sentiment captured by the FSS index explains movements in financial cycle indicators related to credit, asset prices, systemic risk, and monetary policy rates. Finally, our results show that the sentiment in central banks’ communications is a useful predictor of banking crises—a one percentage point increase in FSS is followed by a twenty-nine percentage point increase in the probability of a crisis.

This article studies insider trading quantities and dollar profits to measure the benefits insiders extract from their superior information. Dollar profits are economically small for a typical insider, the median insider earning $464 per year. The correlation between dollar profits and percentage returns is moderate, because returns are negatively correlated with trade size and frequency. We show that these correlations vary with proxies for insider preferences, firm-level monitoring, and regulatory scrutiny. As a consequence, variables that predict percentage returns fail to predict dollar profits, and past dollar profits are negatively related to future returns. Our work suggests that dollar profits are a better measure for corporate governance applications of insider trading.

We present evidence of first impression bias among finance professionals in the field. Equity analysts’ forecasts, target prices, and recommendations suffer from first impression bias. If a firm performs particularly well (poorly) in the year before an analyst follows it, that analyst tends to issue optimistic (pessimistic) evaluations. Consistent with negativity bias, we find that negative first impressions have a stronger effect than positive ones. The market adjusts for analyst first impression bias with a lag. Finally, our findings contribute to the literature on experience effects. We show that a set of professionals in the field, equity analysts, apply U-shaped weights to their sequence of past experiences, with greater weight on first experiences and recent experiences than on intermediate ones.

The level of diseconomies of scale in asset management has important implications for tests of manager skill and the expected level of performance persistence. To identify the causal impact of fund size on future returns, we exploit the fact that small differences in returns can cause discrete changes in Morningstar ratings that, in turn, generate discrete differences in fund size. Using our regression discontinuity approach, we find that ratings significantly increase fund size, but that fund size has a negligible effect on fund returns. Within Berk and Green’s (2004) model, the absence of meaningful fund-level diseconomies of scale implies that the lack of performance persistence arises from a lack of fund manager skill. Alternatively, the lack of performance persistence may arise from competitive pressures outside of their model.

We study whether and how publicizing internal information affects the value of financial markets to the real economy. By publicizing corporate filings, the Securities and Exchange Commission’s EDGAR (Electronic Data Gathering, Analysis, and Retrieval) web platform reduces the cost of acquiring internal information for outsiders and so makes it relatively less attractive to gather external information. We find that the staggered introduction of EDGAR reduced the sensitivity of firm investment to prices, consistent with prices being less informative to managers due to the crowding out of external information gathering. This crowding out effect is stronger when outsiders’ incentives for gathering information are stronger and for firms that rely more on external information. Our findings suggest that policies designed to “level the playing field” by publicizing internal information can have significant unintended consequences by reducing the informativeness of prices for real decisions.

This article shows that postcrisis stress tests have negative effects on entrepreneurship and innovation at young firms. Exploiting unique data on business-related home equity loans in Home Mortgage Disclosure Act, I show that stress-tested banks strongly cut small business loans secured by home equity, an important source of financing for entrepreneurs. Lower credit supply leads to a relative decline in entrepreneurship in counties with higher exposure to stress-tested banks. The decline is stronger in sectors with a higher share of young firms using home equity financing, that is, in which the reduction in credit hits hardest. More-exposed counties also see a decline in young firms’ patent applications as well as labor productivity, reflecting young firms’ disproportionate contribution to growth.

We examine how cross-country differences in capital regulations shape the structure of global lending syndicates. Using globally syndicated loans extended by banks from forty-four countries, we find that strictly regulated banks participate more in syndicates originated by lead lenders facing less stringent capital regulations. The resulting lending syndicates extend loans to riskier borrowers, charge higher spreads, forego covenants more frequently, and incur higher default rates. Such syndication activity also facilitates the access to credit by riskier corporations and exposes both participants and lead arrangers to greater systemic risk. Overall, our finding is consistent with the explanation that strictly regulated banks rely on the expertise of loosely regulated banks to procure risky deals outside the border.