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When the Rules Change: Adaptive Signal Extraction via Kalman Filtering and Markov-Switching Regimes

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  • Sungwoo Kang

Abstract

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.

Suggested Citation

  • Sungwoo Kang, 2026. "When the Rules Change: Adaptive Signal Extraction via Kalman Filtering and Markov-Switching Regimes," Papers 2601.05716, arXiv.org, revised Feb 2026.
    • Handle: RePEc:arx:papers:2601.05716
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