Multi-kernel property in high-frequency price dynamics under Hawkes model

This study investigates and uses multi-kernel Hawkes models to describe a high-frequency mid-price process. Each kernel represents a different responsive speed of market participants. Using the conditional Hessian, we examine whether the numerical optimizer effectively finds the global maximum of th...

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Bibliographic Details
Published in:Studies in nonlinear dynamics and econometrics 2024-09, Vol.28 (4), p.605-624
Main Author: Lee, Kyungsub
Format: Article
Language:English
Subjects:
Hawkes model
high-frequency data
Mathematical functions
Mathematical models
multi-kernel
Nonlinear systems
Prices
responsiveness
Stock exchanges
stock price dynamics
Stock prices
Ultrahigh frequencies
Very high frequencies
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Summary:This study investigates and uses multi-kernel Hawkes models to describe a high-frequency mid-price process. Each kernel represents a different responsive speed of market participants. Using the conditional Hessian, we examine whether the numerical optimizer effectively finds the global maximum of the log-likelihood function under complicated modeling. Empirical studies that use stock prices in the US equity market show the existence of multi-kernels classified as ultra-high-frequency (UHF), very-high-frequency (VHF), and high-frequency (HF). We estimate the conditional expectations of arrival times and the degree of contribution to the high-frequency activities for each kernel.
ISSN:1558-3708
1081-1826
1558-3708
DOI:10.1515/snde-2022-0049