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Forecasting Prices from Level-I Quotes in the Presence of Hidden LiquidityMarco AvellanedaNew York University (NYU) - Courant Institute of Mathematical Sciences; Finance Concepts LLC Josh ReedNew York University (NYU) - Department of Information, Operations, and Management Sciences Sasha StoikovCornell Financial Engineering Manhattan June 29, 2011 Algorithmic Finance, Vol. 1, No. 1, 2011 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 of 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 the hidden liquidity in a market based on high-frequency data. We illustrate the approach with an empirical study of a few liquid stocks using quotes from various exchanges.
Number of Pages in PDF File: 10 Keywords: High frequency data, order book modeling, financial engineering, diffusion limit, hidden liquidity, market microstructure JEL Classification: C44, C51, C32 Accepted Paper SeriesDate posted: October 14, 2010 ; Last revised: October 11, 2012Suggested CitationContact Information
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