From Data Acquisition to Lag Modeling: Quantitative Exploration of A-Share Market with Low-Coupling System Design
Abstract
We propose a novel two-stage framework to detect lead-lag relationships in the Chinese A-share market. First, long-term coupling between stocks is measured via daily data using correlation, dynamic time warping, and rank-based metrics. Then, high-frequency data (1-, 5-, and 15-minute) is used to detect statistically significant lead-lag patterns via cross-correlation, Granger causality, and regression models. Our low-coupling modular system supports scalable data processing and improves reproducibility. Results show that strongly coupled stock pairs often exhibit lead-lag effects, especially at finer time scales. These findings provide insights into market microstructure and quantitative trading opportunities.
Keywords
Cite
@article{arxiv.2506.19255,
title = {From Data Acquisition to Lag Modeling: Quantitative Exploration of A-Share Market with Low-Coupling System Design},
author = {Jianyong Fang and Sitong Wu and Junfan Tong},
journal= {arXiv preprint arXiv:2506.19255},
year = {2025}
}
Comments
11 pages, 16 figures. Includes system architecture, empirical results, and lead-lag detection methods. Code available upon request