Forecasting prices from level-I quotes in the presence of hidden liquidity

Marco Avellaneda, Josh Reed, Sasha Stoikov
2011 Algorithmic Finance  
Bid and ask sizes at the top of the order book provide information on short-term price moves. Drawing from classical descriptions of the order book in terms of queues and order-arrival rates (Smith et al (2003) ), we consider a diffusion model for the evolution of the best bid/ask queues. We compute the probability that the next price move is upward, conditional on the best bid/ask sizes and an additional parameter, the hidden liquidity of the market. We provide closed-form solutions for the
more » ... olutions for the probability in some important special cases. The model can be useful, among other things, to rank trading venues in terms of the "information content" of their quotes and to estimate the hidden liquidity in a market based on high-frequency data. We illustrate the * Cornell Financial Engineering Manhattan, corresponding author, approach with an empirical study of a few liquid stocks using quotes from various exchanges.
doi:10.3233/af-2011-004 fatcat:jsfznu7bn5fdlg75kappcxayqi