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.

The Dodd-Frank Act mandates that certain standard over-the-counter (OTC) derivatives must be traded on swap execution facilities (SEFs). Using message-level data, we provide a granular analysis of dealers’ and customers’ trading behavior on the two largest dealer-to-customer SEFs for index credit default swaps (CDS). On average, a typical customer contacts few dealers when seeking liquidity. A theoretical model shows that the benefit of competition through wider order exposure is mitigated by a winner’s curse problem and dealer-customer relationships. Consistent with the model, we find that order size, market conditions, and customer-dealer relationships are important empirical determinants of customers’ choice of trading mechanism and dealers’ liquidity provision.

We characterize the dynamic fragmentation of U.S. equity markets using a unique data set that disaggregates dark transactions by venue types. The “pecking order” hypothesis of trading venues states that investors “sort” various venue types, putting low-cost-low-immediacy venues on top and high-cost-high-immediacy venues at the bottom. Hence, midpoint dark pools on top, non-midpoint dark pools in the middle, and lit markets at the bottom. As predicted, following VIX shocks, macroeconomic news, and firms’ earnings surprises, changes in venue market shares become progressively more positive (or less negative) down the pecking order. We further document heterogeneity across dark venue types and stock size groups.

We find large overnight returns with no abnormal variance before nonfarm payrolls, ISM, and GDP announcements, similar to the pre-FOMC returns. To explain this common pattern, we propose a two-risk model with the uncertainty about the magnitude of the impending news’ market impact as an additional risk, and link the pre-announcement return directly to the accumulation of heightened uncertainty and its later resolution prior to the announcement. We empirically test and verify the model’s distinct predictions on the joint intertemporal behavior of return, variance, and particularly VIX – a gauge of impact uncertainty by our model, surrounding macroeconomic announcements.