Regime Detection Models

Regime detection models attempt to identify different market environments, such as bull markets, bear markets, or high-volatility phases. These models analyze variables like trend strength, volatility, correlations, or macro indicators to classify current conditions. Once a regime is identified, strategies can adapt exposure. For example, reducing risk during unstable periods or emphasizing Momentum in trending markets. Regime models acknowledge that markets are not stationary. Relationships between signals and returns change over time. While regime detection improves adaptability, it is imperfect. False signals and delayed recognition are unavoidable. Effective implementations use regime awareness as a risk overlay rather than a precise timing tool.