From Data Acquisition to Lag Modeling: Quantitative Exploration of A-Share Market with Low-Coupling System Design
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908418891055104 |
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| author | Fang, Jianyong Wu, Sitong Tong, Junfan |
| author_facet | Fang, Jianyong Wu, Sitong Tong, Junfan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_19255 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Data Acquisition to Lag Modeling: Quantitative Exploration of A-Share Market with Low-Coupling System Design Fang, Jianyong Wu, Sitong Tong, Junfan Computational Finance Statistical Finance 62M10, 62P05, 91G70 I.2.6; I.5.1; J.4 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. |
| title | From Data Acquisition to Lag Modeling: Quantitative Exploration of A-Share Market with Low-Coupling System Design |
| topic | Computational Finance Statistical Finance 62M10, 62P05, 91G70 I.2.6; I.5.1; J.4 |
| url | https://arxiv.org/abs/2506.19255 |