We argue that competition between dealers in a classic dealer market is intertemporal: A trader identifies a particular dealer and negotiates a final price with only the intertemporal threat to switch dealers imposing pricing discipline on the dealer. In this kind of market structure, we show that dealers will offer greater price improvement to more regular customers, and, in turn, these customers optimally choose to submit larger orders. Hence, price improvement and trade size should be negatively correlated in a dealer market. We confirm our model's predictions using unique data from the London Stock Exchange during 1991.

This article uses unique data from the London Stock Exchange to examine how trader anonymity and market liquidity affect dealers' decisions about where to place interdealer trades. During our sample period, dealers could trade with each other in the direct, nonanonymous public market or use one of four anonymous brokered trading systems. Surprisingly, we find that adverse selection is less prevalent in the anonymous brokered markets. We show that this pattern can be explained by the way dealers “price” the adverse selection risk inherent in trading with other dealers. We also relate our findings to recent changes in dealer markets.

We show that when a continuous dark pool is added to a limit order book that opens illiquid, book and consolidated fill rates and volume increase, but spread widens, depth declines, and welfare deteriorates. The adverse effects on market quality and welfare are mitigated when book-liquidity builds but so are the positive effects on trading activity. All effects are stronger when traders’ valuations are less dispersed, access to the dark pool is greater, horizon is longer, and relative tick size larger.

We use unique data from the London Stock Exchange to test whether interdealer trade facilitates inventory risk sharing among dealers. We develop a methodology that focuses on periods of “extreme” inventories—inventory cycles. We further distinguish between inventory cycles that are unanticipated and those that are anticipated because of “worked” orders. The pattern of interdealer trade during inventory cycles matches theoretical predictions for the direction of trade and the inventories of trade counterparts. We also show that London dealers receive higher trading revenues for taking larger positions.

We demonstrate that off-exchange (wholesaler) executions provide significant cost savings to retail investors. Wholesaler concentration has raised regulatory concerns; however, we show that the largest wholesalers offer the lowest costs due to economies of scale. The entry of a new large wholesaler reduces incumbent scale economies, resulting in higher execution costs. Most retail brokers route to multiple wholesalers and actively monitor their performance, rewarding those offering lower execution costs with more volume. While retail investors benefit from the current landscape across all stocks, those trading small stocks benefit the most.

We examine short selling in US stocks based on new SEC-mandated data for 2005. There is a tremendous amount of short selling in our sample: short sales represent 24% of NYSE and 31% of Nasdaq share volume. Short sellers increase their trading following positive returns and they correctly predict future negative abnormal returns. These patterns are robust to controlling for voluntary liquidity provision and for opportunistic risk-bearing by short sellers. The results are consistent with short sellers trading on short-term overreaction of stock prices. A trading strategy based on daily short-selling activity generates significant positive returns during the sample period.

We examine the effects of the Securities and Exchange Commission (SEC)‐mandated temporary suspension of short‐sale price tests for a set of Pilot securities. While short‐selling activity increases both for NYSE‐ and Nasdaq‐listed Pilot stocks, returns and volatility at the daily level are unaffected. NYSE‐listed Pilot stocks experience more symmetric trading patterns and a slight increase in spreads and intraday volatility after the suspension while there is a smaller effect on market quality for Nasdaq‐listed Pilot stocks. The results suggest that the effect of the price tests on market quality can largely be attributed to distortions in order flow created by the price tests themselves.

Studying a comprehensive sample of stocks from the U.S. OTC market, we show that this market is a large and diverse trading environment with a rich set of regulatory and disclosure regimes, comprising venue rules and state laws beyond SEC regulation. We exploit this institutional richness to show that OTC firms subject to stricter regulatory regimes and disclosure requirements have higher market quality (higher liquidity and lower crash risk). Our analysis points to an important trade-off in regulating the OTC market and protecting investors: lowering regulatory requirements reduces the compliance burden for smaller firms, but it also reduces market quality. Received July 26, 2013; editorial decision July 8, 2017 by Editor Itay Goldstein.

Based on a survey of American Finance Association members, we analyze how demographics, time allocation, production mechanisms, and institutional factors affect research production during the pandemic. Consistent with the literature, research productivity falls more for women and faculty with young children. Independently, and novel, extra time spent on teaching (much more likely for women) negatively affects research productivity. Also novel, concerns about feedback, isolation, and health have large negative research effects, which disproportionately affect junior faculty and PhD students. Finally, faculty who express greater concerns about employers’ finances report larger negative research effects and more concerns about feedback, isolation, and health.

After a natural experiment is first used, other researchers often reuse the setting, examining different outcome variables. We use simulations based on real data to illustrate the multiple hypothesis testing problem that arises when researchers reuse natural experiments. We then provide guidance for future inference based on popular empirical settings including difference‐in‐differences, instrumental variables, and regression discontinuity designs. When we apply our guidance to two extensively studied natural experiments, business combination laws and the Regulation SHO pilot, we find that many results that were statistically significant using single hypothesis testing do not survive corrections for multiple hypothesis testing.