Forecasting Prices from Level-I Quotes in the Presence of Hidden Liquidity
New York University (NYU) - Courant Institute of Mathematical Sciences; Finance Concepts LLC
New York University (NYU) - Department of Information, Operations, and Management Sciences
Cornell Financial Engineering Manhattan
June 29, 2011
Algorithmic Finance, Vol. 1, No. 1, 2011
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
Date posted: October 14, 2010 ; Last revised: October 11, 2012
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