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Modeling High Frequency Market Order Dynamics Using Self-Excited Point Process


Howard Howan Stephen Shek


Stanford University

September 25, 2011


Abstract:     
This paper extends the self-excited point process framework to model conditional arrival intensities of buy and sell orders of listed stocks. The cross-excitation of market orders is modeled explicitly such that buy size and buy side order book cumulative volume can affect the sell order intensity, and vice versa. Different variations of the framework are estimated by using method of maximum likelihood estimation, using a recursive application of the log-likelihood functions derived in this paper. Results indicate that by incorporating an order imbalance measure related to the probability weighted cumulative queue volume at the bid and ask sides of the market, one can improve the overall model goodness-of-fit significantly.

Number of Pages in PDF File: 22

Keywords: High Frequency Data, Point Process, Limit Order Book

JEL Classification: C10, C32, C46, C52, C80, G10, G17

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Date posted: August 31, 2010 ; Last revised: September 26, 2011

Suggested Citation

Shek, Howard Howan Stephen, Modeling High Frequency Market Order Dynamics Using Self-Excited Point Process (September 25, 2011). Available at SSRN: http://ssrn.com/abstract=1668160 or http://dx.doi.org/10.2139/ssrn.1668160

Contact Information

Howard Howan Stephen Shek (Contact Author)
Stanford University ( email )
Stanford, CA 94305
United States
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