Dark Markets and Hidden Liquidity

There is considerable empirical evidence that suggests that order exposure in limit-order markets can increase, while shielding ones trading interests from public view can substantially decrease transaction costs. More and more securities markets are thus providing hidden liquidity as a strategic trade-tool to investors, either by virtue of “dark” exchanges with limited/zero pre-trade transparency like Dark Pools or by introducing  Iceberg Orders on traditional exchanges.

Several contributions to optimal trading in dark markets have recently been made by Berlin researchers, especially on

  • optimal portfolio liquidation using dark pools
  • optimal display of iceberg orders
  • market impact of limit orders

Dark pools are alternative trading venues that differ significantly from traditional exchanges. Most importantly, the liquidity available is not quoted, making trade execution uncertain and unpredictable. Moreover, dark pools do not determine prices. Instead, they monitor the prices determined by the classical exchanges and settle trades in the dark pool only if possible at these prices. Thus, trades in the dark pool have no or less price impact. Kratz and Schöneborn (2011) analyze trade execution when trading is possible both at the classical exchange as well as in the dark pool. Their model captures most of the key characteristics of dark pools and allows for (semi-)explict representations of optimal trade execution strategies.

Iceberg Orders are limit orders that are only partly displayed in the order book with the hidden part losing its time priority over the displayed part. Just like dark pools, investors using iceberg orders face a trade-off between a reduced market impact and an increased execution uncertainty. Optimal display sizes for Iceberg Orders when investors maximize expected relative execution prices are analyzed in Cebiroglu and Horst (2011). Suggesting a new way of measuring the impact of limit orders (openly displayed), they show that trade execution can be significantly improved by implementing proper display strategies. Hautsch and Huang (2011b) propose an econometric framework to identify the existence of hidden orders in the market exploiting order message data. Their framework allows analyzing whether and how hidden orders are placed in dependence of the state of the market.

The quantification of the market impact of limit orders is essential for optimal order execution strategies. Indeed, passive order placement through limit orders can incur significant market impact even if the order is not been executed. Hautsch and Huang (2011a) introduce an econometric model for order book dynamics which allows predicting an order’s short-run and long-run market impact. They empirically show that limit orders have significant price impacts with the strength and direction of quote responses depending on the incoming orders’ aggressiveness, their size and the state of the book. 


Selected Publications