Do Dark Pools Harm Price Discovery?

Dark pools are equity trading systems that do not publicly display orders. Dark pools offer potential price improvements but do not guarantee execution. Informed traders tend to trade in the same direction, crowd on the heavy side of the market, and face a higher execution risk in the dark pool, relative to uninformed traders. Consequently, exchanges are more attractive to informed traders, and dark pools are more attractive to uninformed traders. Under certain conditions, adding a dark pool alongside an exchange concentrates price-relevant information into the exchange and improves price discovery. Improved price discovery coincides with reduced exchange liquidity

What is the Optimal Trading Frequency in Financial Markets?

This paper 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

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

What is the Optimal Trading Frequency in Financial Markets?

This paper 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.Asimple 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

Bilateral trading in divisible double auctions

Existing models of divisible double auctions typically require three or more traders—when there are two traders, the usual linear equilibria imply market breakdowns unless the traders’ values are negatively correlated. This paper characterizes a family of nonlinear ex post equilibria in a divisible double auction with only two traders, who have interdependent values and submit demand schedules. The equilibrium trading volume is positive but less than the first best. Closed-form solutions are obtained in special cases. Moreover, no nonlinear ex post equilibria exist if: (i) there are n≥4 symmetric traders or (ii) there are 3 symmetric traders with pure private values. Overall, our nonlinear equilibria fill the “n=2” gap in the divisible-auction literature and could be a building block for analyzing strategic bilateral trading in decentralized markets. Keywords: Divisible double auctions; Bilateral trading; Bargaining; Ex post equilibriu

Commodities as Collateral

We propose and test a theory of using commodities as collateral for financing. Under capital control and collateral constraint, investors import commodities and pledge them as collateral to earn higher expected returns. Higher collateral demands increase commodity prices and make the inventory–convenience yield relation less negative. Our model illustrates these equilibrium effects and suggests that the violation of covered interest-rate parity is a proxy for collateral demands. Evidence from eight commodities in China and developed markets supports the theoretical predictions. Our findings complement the theory of storage and provide new insights into the financialization of commodity markets

Benchmarks in Search Markets

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

Optimal Issuance under Information Asymmetry and Accumulation of Cash Flows

We study the optimal timing of security issuance to finance a new project when the firm\u27s assets in place have unobservable quality. Stochastic cash flows generated by assets in place reveal information about their quality and simultaneously reduce the required outside funding. A high-quality firm optimally delays issuance unless its accumulated cash or the market belief about its quality is sufficiently high. A low-quality firm does the same and, additionally, issues if market belief and accumulated cash are sufficiently low. Under stated restrictions, the renegotiation-proof optimal security pays outside investors in full before paying anything to original shareholders

A New Perspective on Gaussian Dynamic Term Structure Models

In any canonical Gaussian dynamic term structure model (GDTSM), the conditional forecasts of the pricing factors are invariant to the imposition of no-arbitrage restrictions. This invariance is maintained even in the presence of a variety of restrictions on the factor structure of bond yields. To establish these results, we develop a novel canonical GDTSM in which the pricing factors are observable portfolios of yields. For our normalization, standard maximum likelihood algorithms converge to the global optimum almost instantaneously. We present empirical estimates and out-of-sample forecasts for several GDTSMs using data on U.S. Treasury bond yields