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Ebook How large is liquidity risk in an automated auction market?

In economics and finance, the notion of liquidity is generally conceived as the ability to trade quickly a large volume with minimal price impact. In an attempt to grasp the concept more precisely, Kyle (1985) identifies three dimensions of liquidity: tightness (reflected in the bidask spread), depth (the amount of one-sided volume that can be absorbed by the market without causing a revision of the bid-ask prices), and resiliency (the speed of return to equilibrium).

In modern automated auction markets, the liquidity supply solely depends on the state of the electronic order book which consists of previously entered, non-executed limit buy and sell orders. This set of standing orders determines the price-volume relationship that a trader who requires immediacy of execution is facing. If few limit buy or sell orders are present in the system or if many orders are present but for small trade sizes only, liquidity is low and marketable limit order trades may incur considerable price impacts. For example, Harris (2002) provides a complete taxonomy of the kinds of trades that can be submitted to exchanges and their impact on market liquidity.

Broadly speaking and focusing solely on order books, liquidity providers (patient investors) submit non-aggressive limit orders, i.e. limit orders which do not face immediate execution but which provide liquidity to the system by filling the order book. Liquidity demanders (impatient traders) submit market orders which are executed against standing limit orders and which thus deplete the order book and decrease the overall liquidity.1 Recent studies which focus on the interaction and dynamics of market orders vs limit orders in automated auctions include Biais, Hillion, and Spatt (1995), Handa and Schwartz (1996), Ahn, Bae, and Chan (2001) or Beltran, Giot, and Grammig (2002).

Due to the interaction between limit and market orders, most studies conclude that there exists a dynamical equilibrium between limit order trading and transitory volatility. Examples of impatient traders include traders who wish to transact near the close of the trading session (so that the price of their trade is not far from the official closing price), see Cushing and Madhavan (2000), or momentum traders who are keen on entering immediate long or short positions (Keim and Madhavan, 1997). In all cases, this behavior leads to increased volatility and trading costs.

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