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.

We study the design of credit default swaps (CDS) auctions, which determine the payments by CDS sellers to CDS buyers following defaults of bonds. Using a simple model, we find that the current design of CDS auctions leads to biased prices and inefficient allocations. This is because various restrictions imposed in CDS auctions prevent certain investors from participating in the price discovery and allocation process. The imposition of a price cap or floor also gives dealers large influence on the final auction price. We propose an alternative double auction design that delivers more efficient price discovery and allocations.

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.

We show that a linear pure strategy equilibrium may not exist in the model of Madrigal (1996), contrary to the claim of the original paper. This is because Madrigal's characterization of a pure strategy equilibrium omits a second‐order condition. If the nonfundamental speculator's information about noise trading is sufficiently precise, a linear pure strategy equilibrium fails to exist. In parameter regions where a pure strategy equilibrium does exist, we identify a few calculation errors in Madrigal (1996) that result in misleading implications.

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.