Using trade-level data, we study whether brokers play a role in spreading order flow information. We focus on large portfolio liquidations, which result in temporary drops in stock prices, and identify the brokers that intermediate these trades. We show that these brokers' best clients tend to...

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....

We propose a new model of trading in OTC 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...

Competition among trading platforms has considerably reduced trading fees in stock markets. We show that this evolution is not necessarily beneficial to investors. Obviously it increases gains from trade when a trade happens. Less obviously, it can induce investors to post limit orders with a...

Using trader-resolved data, we document lead-lag relationships between groups of investors in the foreign exchange market. Because these relationships are systematic and persistent, order flow is predictable from trader-resolved order flow. We thus propose a generic method to exploit trader...

We examine the effect of learning of uninformed traders in a dynamic limit order market with asymmetric and short-lived information. We show that the learning is effective and valuable with respect to information acquisition, forecasting and buy-sell decision accuracies, and profit opportunity...