Knowledge that Transforms

We study the transmission of financial news and opinions through social interactions among retail investors in the United States. We identify a series of plausibly exogenous shocks, which cause “treated investors” to trade abnormally. We then trace the “contagion” of abnormal trading activity from the treated investors to their neighbors and their neighbors’ neighbors. Coupled with methodology drawn from epidemiology, our setting allows us to estimate the rate of communication and how it varies with the characteristics of the underlying investor population.

We introduce diagnostic expectations into a standard setting of price formation in which investors learn about the fundamental value of an asset and trade it. We study the interaction of diagnostic expectations with learning from prices and speculation (buying for resale). With diagnostic (but not with rational) expectations, these mechanisms lead to price paths exhibiting three phases: initial underreaction, then overshooting (the bubble), and finally a crash. With learning from prices, the model generates price extrapolation as a by-product of beliefs about fundamentals, lasting only as the bubble builds up. When investors speculate, even mild diagnostic distortions generate substantial bubbles.

We examine how consumer credit affects entrepreneurship by linking three million earnings and pass-through tax records to credit reports. In the cross-section, we show that self-employment without employees and employer firm ownership increase monotonically with credit limits and credit scores. We then isolate individuals who have had discrete increases in credit limits after the exogenous removal of bankruptcy flags to measure the effects of personal credit on entrepreneurship. Following bankruptcy flag removal, individuals are more likely to start a new employer business and borrow extensively. Those who own businesses with employees borrow $40,000 more after bankruptcy flag removal, a 33% gain relative to the sample average.

We identify the broker each corporate insider trades through, and find that analysts and mutual fund managers affiliated with such “inside brokers” have a substantial information advantage on the insider’s firm. Affiliated analysts issue more accurate earnings forecasts, and affiliated mutual funds trade the insider’s stock more profitably than their peers, following insider trades through their brokerage. Notably, this advantage persists well after these insider trades are publicly disclosed. Our results challenge the prevalent perception that information asymmetry arising from insider trading is acute only before trade disclosure, and suggest that brokers facilitating these trades are in a position to exploit this asymmetry.

I examine blockchain congestion episodes caused by more than 4,400 triggers for ransomware attacks over a two-year period. When demand for settlement exceeds blockchain capacity, blockchain users engage in fee competition to prioritize their transaction settlement. A typical surge in ransomware activity causes transaction fees to increase by 2.1% and up to 28% in extreme cases. Consistent with theory literature, some users forgo blockchain settlement when transaction fees increase. An event study around an extreme spike in ransomware activity supports the findings of the main analysis.

We analyze the effects of prudential regulation on short-term interest rates. The European Market Infrastructure Regulation (EMIR) induces clearing houses (CCPs) to supply large amounts of cash in reverse repurchase agreements (repos). Basel III, in contrast, disincentivizes the borrowing demand by tightening banks’ balance sheet constraints. Using unique regulatory data of CCP investment activity and repo transactions, we find compelling evidence for both the supply and demand channels. The overall effects are decreasing short-term rates and increasing market imbalances in various forms, all of which entail unintended consequences due to the new regulatory framework.

We use a unique sample of corporate bonds guaranteed by the full faith and credit of the US to test recent theories about why asset prices may diverge from fundamental values. A key feature of our study is access to proprietary data on the haircuts, funding costs, and inventory positions of the primary dealers making markets in the individual bonds. The results provide strong support for the cross-sectional implications of the safe-asset, intermediary-constraints, and search-frictions literatures. Furthermore, the results indicate that network topology may also play an important role in explaining mispricing.

Given overall lack of gender diversity in the venture capital and entrepreneurship industry shown in Calder-Wang and Gompers (2017) we ask: What promotes greater gender diversity in hiring? Does diversity lead to better firm performance and higher investment returns? In this paper, using a unique dataset of the gender of venture capital partners’ children, we find strong evidence that when partners have more daughters, the propensity to hire female partners increases. Moreover, our instrumental variable results suggest that increased gender diversity improves deal and fund performance. Lastly, the effects are primarily driven by the gender of senior partners’ children.

We derive an options-pricing formula from recursive preferences and estimate rare disaster probability. The new options-pricing formula applies to far out-of-the-money put options on the stock market when disaster risk dominates, the size distribution of disasters follows a power law, and the economy has a representative agent with a constant-relative-risk-aversion utility function. The formula conforms with options data on the Standard & Poor's (S&P) 500 Index from 1983 to 2018 and for analogous indices for other countries. The disaster probability, inferred from monthly fixed effects, is highly correlated across countries, peaks during the Global Financial Crisis, and forecasts rates of economic growth.

We examine the dynamic relation between firm leverage buildups and real economic activity using U.S. establishment-, firm-, and region-level data. We find that buildups in firm leverage are predictably associated with boom-bust growth cycles: employment grows in the short run but declines in the medium run. While firm leverage buildups are correlated with firm-level expansions, they continue to predict negative future employment growth if we control for firm-level expansions. Buildups in firm leverage predict a tightening of future firm-level financing constraints, and they only predict negative future employment growth if the level of firm leverage is sufficiently high, suggesting that the dynamic relation between firm leverage buildups and employment growth operates through a financial fragility channel. Our results have aggregate implications: regions with larger buildups in firm leverage experience stronger regional boom-bust growth cycles, and they perform significantly worse during national recessions.