Regimes in the Order Flow

2026-09-07

AI Summary

研究使用贝叶斯在线变点检测及其两种扩展方法，实现实时识别纳斯达克上市股票订单流中的结构断裂，以应对金融市场稳定与不稳定期的转换。

Abstract

Financial markets alternate between periods of relative stability and instability, with structural breaks marking the transitions between these regimes. Identifying such breaks in real time is a central requirement for any trading or risk system operating at high frequency. This report studies Bayesian Online Changepoint Detection (BOCPD) and two extensions proposed in the literature, and applies them to the signed order flow of NASDAQ-listed equities.

Problem

• financial markets
• order flow
• structural breaks
• real-time detection

Innovation

• Bayesian Online Changepoint Detection
• signed order flow
• real-time identification