This article studies the impact of increasing trading frequency in financial markets on allocative efficiency. We build and solve a dynamic model of sequential double auctions in which traders trade strategically with demand schedules. Trading needs are generated by time-varying private information about the asset value and private values for owning the asset, as well as quadratic inventory costs. We characterize a linear equilibrium with stationary strategies and its efficiency properties in closed form. Frequent trading (more double auctions per unit of time) allows more immediate asset reallocation after new information arrives, at the cost of a lower volume of beneficial trades in each double auction. Under stated conditions, the trading frequency that maximizes allocative efficiency coincides with the information arrival frequency for scheduled information releases, but can far exceed the information arrival frequency if new information arrives stochastically. A simple calibration of the model suggests that a moderate market slowdown to the level of seconds or minutes per double auction can improve allocative efficiency for assets with relatively narrow investor participation and relatively infrequent news, such as small- and micro-cap stocks.

Size-discovery mechanisms allow large quantities of an asset to be exchanged at a price that does not respond to price pressure. Primary examples include “workup” in Treasury markets, “matching sessions” in corporate bond and CDS markets, and block-trading “dark pools” in equity markets. By freezing the execution price and giving up on market-clearing, size-discovery mechanisms overcome concerns by large investors over their price impacts. Price-discovery mechanisms clear the market, but cause investors to internalize their price impacts, inducing costly delays in the reduction of position imbalances. We show how augmenting a price-discovery mechanism with a size-discovery mechanism improves allocative efficiency.

This article investigates the influence of financial development on patterns of industrial specialization across China’s regions. We find that industrial sectors reliant on access to external finance tend to concentrate in regions with well-developed financial markets. Both foreign direct investment (FDI) and alternative financing channels are shown to play significant roles in shaping patterns of industrial specialization in China. In contrast, proxies for formal financial markets, for example, the banking system and capital markets, have few effects on regional industrial agglomeration. This result remains robust to instrumental variable estimation, alternative model specifications, and controlling for other traditional determinants of regional specialization.

Is coachability a usable concept for startups? Using a dataset on high-growth startups in a prominent university incubator, we show that firm characteristics do predict which firms are likely to follow advice but that these “coachable” firms are not more likely to achieve positive outcomes. The reason is that advice may be rejected either because the firm is stubborn and uncoachable, or because the firm possesses capabilities related to the advice which is hard for outsiders to observe.

Using jumps in stock prices as a proxy for large information shocks, we provide evidence consistent with short-term underreaction in the US equity market. Strategies long (short) stocks with positive (negative) lagged jump returns earn significantly positive returns over the next one- to three-month horizons. The results based on intraday jumps, especially overnight jumps, provide further evidence consistent with underreaction. The underreaction is robust to controlling for other firm characteristics, extends stock return momentum over intermediate to short horizons, and captures market underreaction to information shocks beyond earnings surprises. We further show that limited investor attention contributes to short-term underreaction.

We characterize the role of benchmarks in price transparency of over‐the‐counter markets. A benchmark can raise social surplus by increasing the volume of beneficial trade, facilitating more efficient matching between dealers and customers, and reducing search costs. Although the market transparency promoted by benchmarks reduces dealers' profit margins, dealers may nonetheless introduce a benchmark to encourage greater market participation by investors. Low‐cost dealers may also introduce a benchmark to increase their market share relative to high‐cost dealers. We construct a revelation mechanism that maximizes welfare subject to search frictions, and show conditions under which it coincides with announcing the benchmark.

The role of credit default swaps (CDS) in the 2008 financial crisis has been widely debated among regulators, investors, and researchers. While CDS were blamed for destabilizing the financial system, they remain effective tools for hedging credit risk, especially for major banks, and produce positive informational externalities to market participants. This paper examines whether the introduction of CDS enhances the amount of firm-specific information impounded in stock prices. We use stock return synchronicity to measure the amount of firm-specific information reflected in stock prices, with more firm-specific information being associated with a lower level of synchronicity. We find that a firm’s stock return synchronicity decreases after the commencement of CDS trading. This finding is robust to different model specifications, synchronicity measures, and endogeneity controlling methodologies. Furthermore, the decrease in stock return synchronicity is more pronounced for CDS firms with higher credit risk. Overall, our evidence supports the positive role of CDS in improving informativeness of stock prices.