An order book dependent Hawkes process is estimated via a scalable algorithm for large high-frequency datasets, with out-of-sample tests on four NYSE stocks showing added value from nonlinear order book covariates.
From asymptotic properties of general point processes to the ranking of financial agents
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abstract
We propose a general non-linear order book model that is built from the individual behaviours of the agents. Our framework encompasses Markovian and Hawkes based models. Under mild assumptions, we prove original results on the ergodicity and diffusivity of such system. Then we provide closed form formulas for various quantities of interest: stationary distribution of the best bid and ask quantities, spread, liquidity fluctuations and price volatility. These formulas are expressed in terms of individual order flows of market participants. Our approach enables us to establish a ranking methodology for the market makers with respect to the quality of their trading.
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Estimation of an Order Book Dependent Hawkes Process for Large Datasets
An order book dependent Hawkes process is estimated via a scalable algorithm for large high-frequency datasets, with out-of-sample tests on four NYSE stocks showing added value from nonlinear order book covariates.