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

Article type: Research Article

Authors: Avellaneda, Marco^a | Reed, Josh^b | Stoikov, Sasha^c

Affiliations: [a] Courant Institute, New York University and Finance Concepts LLC, NY, USA | [b] Stern School of Business, New York University, NY, USA | [c] Cornell Financial Engineering Manhattan, NY, USA. Email: [email protected]

Abstract: 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, the hidden liquidity in the market and the correlation between changes in the bid/ask sizes. The model can be useful, among other things, to rank trading venues in terms of the “information content” of their quotes and to estimate hidden liquidity in a market based on high-frequency data. We illustrate the approach with an empirical study of a few stocks using quotes from various exchanges.

DOI: 10.3233/AF-2011-004

Journal: Algorithmic Finance, vol. 1, no. 1, pp. 35-43, 2011