This paper considers the role of high-frequency trading in a dynamic limit order market. Fast traders׳ ability to revise their quotes quickly after news arrivals helps to reduce the inefficiency that is rooted in the risk of being picked off, which increases trade. However, their presence induces slow traders to strategically submit limit orders with a lower execution probability, thereby reducing trade. Because speed is a source of market power, it enables fast traders to extract rents from other market participants and triggers a costly arms race that reduces social welfare. The model generates a number of testable implications concerning the effects of high-frequency trading in limit order markets.

This paper investigates the role of informed trading in a fragmented financial market under the absence of inter-market price priority. Due to frictions in traders’ market access, liquidity providers on alternative trading platforms can be exposed to an increased adverse selection risk. As a consequence, the main market will dominate (display better quotes) frequently albeit charging considerably higher transaction fees. The empirical analysis of a dataset of trading in French and German stocks suggests that trades on Chi-X Europe, a low-cost trading platform, carry significantly more private information than those executed in the Primary Markets. Consistent with our theory, we find a negative relationship between the competitiveness of Chi-X Europe’s quotes and this excess adverse selection risk faced by liquidity providers in the cross-section.

Using data on Spanish mutual funds, we show that bank-affiliated funds provide funding support to their parent company via purchases of bonds in the primary market. Support from affiliated funds is more sizeable in crisis times and for riskier banks. These trades generate negative abnormal returns and thus benefit banks at the expense of fund investors. To minimize negative effects on their asset management business, banks concentrate the burden of funding support in funds without performance fees and those catering to retail investors. We provide evidence consistent with funding support helping to limit credit rationing over the 2008–2012 period.

We propose a model of lending, payments choice, and privacy in the digital economy. While digital payments enable merchants to sell goods online, they reveal information to their lender. Cash guarantees anonymity, but limits distribution to less efficient offline venues. In equilibrium, merchants trade off the efficiency gains from online distribution (with digital payments) and the informational rents from staying anonymous (with cash). While new technologies can reduce the privacy concerns associated with digital payments, they also redistribute surplus from the lender to merchants. Hence, privacy enhancements do not always improve welfare.

ABSTRACT We propose a new model of trading in over‐the‐counter markets. Dealers accumulate inventories by trading with end‐investors and trade among each other to reduce their inventory holding costs. Core dealers use a more efficient trading technology than peripheral dealers, who are heterogeneously connected to core dealers and trade with each other bilaterally. Connectedness affects prices and allocations if and only if the peripheral dealers' aggregate inventory position differs from zero. Price dispersion increases in the size of this position. The model generates new predictions about the effects of dealers' connectedness and dealers' aggregate inventories on prices.