We show whether central clearing of a particular class of derivatives lowers counterparty risk. For plausible cases, adding a central clearing counterparty (CCP) for a class of derivatives such as credit default swaps reduces netting efficiency, leading to an increase in average exposure to counterparty default. Further, clearing different classes of derivatives in separate CCPs always increases counterparty exposures relative to clearing the combined set of derivatives in a single CCP. We provide theory as well as illustrative numerical examples of these results that are calibrated to notional derivatives position data for major banks.

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.

The Federal Reserve uses (reverse) auctions to implement its purchases of Treasury bonds in quantitative easing (QE). To evaluate dealers’ offers across multiple bonds, the Fed relies on its internal yield curve model, fitted to secondary market bond prices. From November 2010 to September 2011, a one standard deviation increase in the cheapness of a Treasury bond (how much the market price of the bond is below a model-implied value) increases the Fed’s purchase quantity of that bond by 276 million and increases the auction costs on that bond by 2.6 cents per $100 par value, controlling for standard covariates. Our results suggest that the Fed harvests gains from trades by purchasing undervalued bonds, but strategic dealers extract some profits because the Fed’s relative values can be partly inferred from price data.

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 impact of FinTech competition in payment services when a monopolist bank uses payment data to learn about consumers’ credit quality. Competition from FinTech payment providers disrupts this information spillover. The bank’s price for payment services and its loan offers are affected. FinTech competition promotes financial inclusion, may hurt consumers with a strong bank preference, and has an ambiguous effect on the loan market. Both FinTech data sales and consumer data portability increase bank lending, but the effects on consumer welfare are ambiguous. Under mild conditions, consumer welfare is higher under data sales than with data portability.

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. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

Postcrisis bank regulations raised market-making costs for bank-affiliated dealers. We show that this can, somewhat surprisingly, improve overall investor welfare and reduce average transaction costs despite the increased cost of immediacy. Bank dealers in OTC markets optimize between two parallel trading mechanisms: market making and matchmaking. Bank regulations that increase market-making costs change the market structure by intensifying competitive pressure from nonbank dealers and incentivizing bank dealers to shift their business activities toward matchmaking. Thus, postcrisis bank regulations have the (unintended) benefit of replacing costly bank balance sheets with a more efficient form of financial intermediation.

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.