Algorithms enable investors to locate trading opportunities, which raises gains from trade. Algorithmic traders can also process information on stock values before slow traders, which generates adverse selection. We model trading in this context and show that, for a given level of algorithmic...

We devel op a dynamic modelof anorder-drivenmarket populated bydiscretionary liquidity traders. These tradersmust trade, yet canchoose the type oforder and are fully strategic in their decision. Traders differ by their impatience: less patient traders are likely to demand liquidity, more patient...

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...

We develop a model in which the speed of reaction to trading opportunities is endogenous. Traders face a trade-off between the benefit of being first to seize a profit opportunity and the cost of attention required to be first to seize this opportunity. The model provides an explanation for...

We study competition between a dealer (OTC) market and a limit order market. In the limit order market, investors can choose to be "makers" (post limit orders) or "takers" (hit limit orders) whereas in the dealer market they must trade at dealers' quotes. Moreover, in the limit order market,...

High-speed market connections and information processing improve the ability to seize trading opportunities, raising gains from trade. They also enable fast traders to process information before slow traders, generating adverse selection, and thus negative externalities. When investing in fast...

High-speed market connections improve investors' ability to search for attractive quotes in fragmented markets, raising gains from trade. They also enable fast traders to observe market information before slow traders, generating adverse selection, and thus negative externalities. When investing...

We develop a dynamic model of a market with two specialized sides: traders posting quotes ("market makers") and traders hitting quotes ("market takers"). Traders monitor the market to seize profit opportunities, generating high frequency liquidity cycles. Monitoring decisions by market-makers...

We consider a multi-period rational expectations model in which risk-averse investors differ in their information on past transaction prices (the ticker). Some investors (insiders) observe prices in real-time whereas other investors (outsiders) observe prices with a delay. As prices are...

Lecture on the first SFB/TR 15 meeting, Gummersbach, July, 18 - 20, 2004: We develop a model of limit order trading in which some traders have better information on future price volatility. As limit orders have option-like features, this information is valuable for limit order traders. We solve...