Knowledge that Transforms

We test whether measures of influence on regulators affect stress-test outcomes. The large trading banks—those most plausibly Too Big to Fail—face the toughest tests. Supervisory stress tests have a greater effect on large trading banks’ portfolios; the large banks respond by making more conservative (initial) capital plans; and, despite their more conservative capital plans, the large banks still fail their tests more frequently than other banks. In contrast, while we find little evidence that political or regulatory connections affect the quantitative element of the stress tests, these connected banks do face less scrutiny under its qualitative dimension.

We examine an undercover Securities and Exchange Commission (SEC) investigation into the manipulation of financial news on social media. While fraudulent news had a direct positive impact on retail trading and prices, revelation of the fraud by the SEC announcement resulted in significantly lower retail trading volume on all news, including legitimate news, on these platforms. For small firms, volume declined by 23.5% and price volatility dropped by 1.3%. We find evidence consistent with concerns of fraud causing the decline in trading activity and price volatility, which we interpret through the lens of social capital, and attempt to rule out alternative explanations. The results highlight the indirect consequences of fraud and its spillover effects that reduce the social network’s impact on information dissemination, especially for small, opaque firms.

Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices, and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that the wider use of big tech credit could reduce the importance of the collateral channel but, at the same time, make lending more reactive to changes in firms’ business activity.

We examine the stock market returns in an environment in which the dates of the central bank’s information supply through public announcements are not prescheduled. We document that positive excess returns are accumulated as early as 3 days before China’s central bank releases the monthly data of monetary aggregates, which may be announced either early or late in a month. In particular, this pre-announcement premium exists only when an announcement arrives late in an announcement cycle. We provide a theoretical framework in which the degree of information acquisition in the market increases as the date approaches the end of an announcement cycle while investors are still waiting for the arrival of an announcement, a hypothesis that receives strong empirical support. We show that the information acquisition channel highlighted in Ai, Bansal, and Han (2022) explains the uncertainty reduction and the positive risk premium before monetary announcements in China.

Using numeric and textual data extracted from over 50,000 finance articles in Social Science Research Network (SSRN) during 2001–19, we examine the relationship between measured qualities and a paper’s readership, eventual outlet, and impact. Conventionality (semantic similarity with existent research) helps boost readership and publication prospects. However, novelty in the forms of emerging topics and databases are associated with better publishing outcomes. Studies that do not easily map into established finance subfields or that introduce nonfinance elements face a higher hurdle. Finally, papers whose research questions span multiple fields are a hard sell, but those building on prior knowledge from multiple fields are valued.

We explore the effects of a “tick size war” in which European trading venues directly competed on the minimum pricing increment in the limit order book, the tick size. We find that venues that reduced their tick size immediately captured market shares of both quoted and executed volume from the exchanges that kept their ticks large. We find that tick size competition improves market quality, reducing trading costs, and increasing market-wide depth and volume. These market quality improvements are strongest in stocks where the bid–ask spread was constrained to one tick, where liquidity providers use the finer pricing grid to engage in price competition.

In the twenty-first century, the most valuable firms in the world are valued primarily for their data. This article describes a set of tools to measure and value data and highlights unanswered questions, where more research is needed.

We document that leased capital accounts for about 20% of total physical productive assets used by US public firms, and its proportion is more than 40% among small and financially constrained firms. The leased capital ratio exhibits a strong countercyclical pattern over business cycles and a positive correlation with cross-sectional idiosyncratic uncertainty. We argue that existing macro models with financial frictions assume that firms cannot rent capital and overlook the effects of leasing activities on business cycle dynamics. We explicitly introduce a buy-versus-lease decision into the Bernanke–Gertler–Gilchrist financial accelerator model setting to demonstrate a novel and quantitatively important economic mechanism: that the increased use of leased capital when financial constraints become tighter in bad states significantly mitigates the financial accelerator mechanism and thus also mitigates the response of macroeconomic variables to negative total factor productivity shocks and risk shocks. We provide strong empirical evidence to support our mechanism.

We examine whether bereavement affects managerial investment decisions in large organizations using the exogenous events of managers’ family deaths. We find evidence that bereaved managers take less risk in separate samples of mutual funds and publicly traded firms. Mutual funds managed by bereaved managers exhibit smaller tracking errors, lower active share measures, and higher portfolio weights on larger stocks after bereavement events. Firms managed by bereaved CEOs exhibit lower capital expenditures and fewer acquisitions after bereavement events. Further analyses support the emotion-driven explanation over other explanations. The risk shifting by bereaved managers has negative implications on the performance of funds and firms that they manage.

We estimate the indirect costs of financial distress due to lost sales by exploiting real estate (RE) shocks and cross-supplier variation in RE assets and leverage. We show that for the same client buying from different suppliers, the client’s purchases from distressed suppliers decline by an additional 13% following a drop in local RE prices. The effect is more pronounced in more competitive industries, manufacturing, durable goods, less-specific goods, and when the costs of switching suppliers are low. Our results suggest that clients reduce their exposure to suppliers in financial distress.