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arXiv · 2604.00346

Forecasting duration in high-frequency financial data using a self-exciting flexible residual point process

Kyungsub Lee
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Abstract

This paper presents a method for forecasting limit order book durations using a self-exciting flexible residual point process. High-frequency events in modern exchanges exhibit heavy-tailed interarrival times, posing a significant challenge for accurate prediction. The proposed approach incorporates the empirical distributional features of interarrival times while preserving the self-exciting and decay structure. This work also examines the stochastic stability of the process, which can be interpreted as a general state-space Markov chain. Under suitable conditions, the process is irreducible, aperiodic, positive Harris recurrent, and has a stationary distribution. An empirical study demonstrates that the model achieves strong predictive performance compared with several alternative approaches when forecasting durations in ultra-high-frequency trading data.

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Kyungsub Lee. 2026-04-01. Forecasting duration in high-frequency financial data using a self-exciting flexible residual point process. https://arxiv.org/abs/2604.00346

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