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

Marco Avellaneda, Josh Reed, Sasha Stoikov

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)35-43
Number of pages9
JournalAlgorithmic Finance
Issue number1
StatePublished - 2011

ASJC Scopus subject areas

  • Finance
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Computational Mathematics


Dive into the research topics of 'Forecasting prices from level-I quotes in the presence of hidden liquidity'. Together they form a unique fingerprint.

Cite this