Marked point processes and intensity ratios for limit order book modeling

Ioane Muni Toke () and Nakahiro Yoshida
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Ioane Muni Toke: MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec - Université Paris-Saclay
Nakahiro Yoshida: Graduate school of mathematics - UTokyo - Tōkyō teikoku daigaku = University of Tokyo [Tokyo]

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Abstract: This paper extends the analysis of Muni Toke and Yoshida (2020) to the case of marked point processes. We consider multiple marked point processes with intensities defined by three multiplicative components, namely a common baseline intensity, a state-dependent component specific to each process, and a state-dependent component specific to each mark within each process. We show that for specific mark distributions, this model is a combination of the ratio models defined in Muni Toke and Yoshida (2020). We prove convergence results for the quasi-maximum and quasi-Bayesian likelihood estimators of this model and provide numerical illustrations of the asymptotic variances. We use these ratio processes in order to model transactions occuring in a limit order book. Model flexibility allows us to investigate both state-dependency (emphasizing the role of imbalance and spread as significant signals) and clustering. Calibration, model selection and prediction results are reported for high-frequency trading data on multiple stocks traded on Euronext Paris. We show that the marked ratio model outperforms other intensity-based methods (such as "pure" Hawkes-based methods) in predicting the sign and aggressiveness of market orders on financial markets.

Date: 2022
New Economics Papers: this item is included in nep-mst
Note: View the original document on HAL open archive server: https://hal.science/hal-02465428v1
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Published in Japanese Journal of Statistics and Data Science , 2022, 5 (1), pp.1-39. ⟨10.1007/s42081-021-00137-9⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02465428

DOI: 10.1007/s42081-021-00137-9

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