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| Format: | Preprint |
| Publié: |
2026
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2601.05716 |
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| _version_ | 1866918354998001664 |
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| author | Kang, Sungwoo |
| author_facet | Kang, Sungwoo |
| contents | Most empirical microstructure research assumes that order flow--return parameters are constant, yet these relationships shift substantially across market regimes. Combining adaptive Kalman filtering, Markov-switching regime identification, and asymmetric response estimation, we characterize regime-dependent investor behavior in the Korean stock market during 2020--2024 using daily transaction data disaggregated by investor type. Three principal findings emerge: foreign investor predictive power increases several-fold during crisis periods relative to bull markets; individual investors chase momentum asymmetrically, reacting far more strongly to positive than to negative shocks; and independent information-theoretic validation corroborates both patterns. Rigorous out-of-sample testing reveals that these in-sample regularities do not generalize reliably, underscoring the need for proper validation methodology in microstructure research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_05716 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | When the Rules Change: Adaptive Signal Extraction via Kalman Filtering and Markov-Switching Regimes Kang, Sungwoo Computational Finance Most empirical microstructure research assumes that order flow--return parameters are constant, yet these relationships shift substantially across market regimes. Combining adaptive Kalman filtering, Markov-switching regime identification, and asymmetric response estimation, we characterize regime-dependent investor behavior in the Korean stock market during 2020--2024 using daily transaction data disaggregated by investor type. Three principal findings emerge: foreign investor predictive power increases several-fold during crisis periods relative to bull markets; individual investors chase momentum asymmetrically, reacting far more strongly to positive than to negative shocks; and independent information-theoretic validation corroborates both patterns. Rigorous out-of-sample testing reveals that these in-sample regularities do not generalize reliably, underscoring the need for proper validation methodology in microstructure research. |
| title | When the Rules Change: Adaptive Signal Extraction via Kalman Filtering and Markov-Switching Regimes |
| topic | Computational Finance |
| url | https://arxiv.org/abs/2601.05716 |