We develop a sequential trade model of Iceberg order execution in a limit order book. The Iceberg-trader has the freedom to expose his trading intentions or (partially) shield the true order size against other market participants. Order exposure can cause drastic market reactions ("market...

We cross-sectionally analyze the presence of aggregated hidden depth and trade volume in the S&P 500 and identify its key determinants. We find that the spread is the main predictor for a stock's hidden dimension, both in terms of traded and posted liquidity. Our findings moreover suggest that...

We develop a model of an order-driven exchange competing for order flow with off-exchange trading mechanisms. Liquidity suppliers face a trade-off between benefits and costs of order exposure. If they display trading intentions, they attract additional trade demand. We show, in equilibrium,...

We develop a model of an order-driven exchange competing for order flow with off-exchange trading mechanisms. Large investors can trade in either the primary market or the off-exchange market and induce liquidity externalities. Liquidity suppliers in the primary market face a trade-off between...

In limit order book markets, traders face the problem whether to display or hide their orders. While hiding reduces exposure impact, exposing can increase execution priority. Based on order flow dynamics, we develop a structural model that captures this trade-off. A central aspect of this work...

We take advantage of a unique data set, NASDAQ ModelView, to empirically analyze the determinants and the impact of hidden liquidity on public exchanges. Our findings are as follows. First, the cross-sectional presence of hidden liquidity is well explained by observable and readily available...