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Modeling aggressive market order placements with Hawkes factor models
Hai-Chuan Xu1,2, Wei-Xing Zhou1,2,3
1Research Center for Econophysics, East Chine University of Science and Technology, Shanghai, China.
Plos One
|January 11, 2020
Summary
Aggressive market orders drive stock price changes. A new Hawkes process model shows self-excitation, not cross-excitation, causes order clustering, improving market microstructure analysis.
Area of Science:
- Quantitative Finance
- Financial Market Microstructure
- Econometrics
Background:
- Stock market prices are influenced by the arrival of market orders.
- Understanding the dynamics of order arrivals is crucial for market microstructure analysis.
Purpose of the Study:
- To develop and calibrate a bivariate marked Hawkes process model for aggressive market order arrivals.
- To analyze the drivers of endogenous submission clustering in stock markets.
Main Methods:
- Introduction of a bivariate marked Hawkes process model.
- Calibration of the model using data from the Shenzhen Stock Exchange.
- Comparison of different kernel functions (smooth cut-off vs. monotonous exponential).
Main Results:
- A smooth cut-off exponential kernel provides superior model calibration compared to a monotonous exponential kernel.
- The exogenous baseline intensity successfully explains the U-shaped intraday pattern of order arrivals.
- Empirical evidence indicates that self-excitation is the primary driver of endogenous order submission clustering.
Conclusions:
- The proposed Hawkes process model effectively captures the dynamics of aggressive market orders.
- Self-excitation plays a more significant role than cross-excitation in generating order clustering.
- Findings enhance the understanding of stock market microdynamics and price formation.
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