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

2026/04/01 by Kyungsub Lee · 1 voice
Economics, Econometrics and Finance · Mathematics · #q-fin.ST #q-fin.TR #stat.AP

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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.

Citations

• Limit Order Book Dynamics and Order Size Modelling Using Compound Hawkes Process
• Hawkes processes in finance
• Critical reflexivity in financial markets: a Hawkes process analysis
• Econometrics of Financial High-Frequency Data
• Spectra of some self-exciting and mutually exciting point processes

Discussions

• Kyungsub Lee: Forecasting duration in high-frequency financial data using a self-exciting flexible residual point process https://arxiv.org/abs/2604.00346 https://arxiv.org/pdf/2604.00346 https://arxi [bsky, 0 points, 0 comments]

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