regime-detection

Market regime detection applies Hidden Markov Models and structural-break tests to classify equities, FX, and multi-asset data into bull, bear, or sideways states, outputting real-time state probabilities for allocation adjustments.

Regime-switching analysis for backtesting applies structural-break tests and Markov-switching models to historical price data, generating regime labels and state probabilities to evaluate strategy performance across varying volatility environments.

Yes, regime detection supports live monitoring by producing real-time state probabilities for equities, FX, and multi-asset portfolios, enabling dynamic risk budget and hedging adjustments based on the current volatility regime.

Structural-break tests detect abrupt shifts in market behavior, while Hidden Markov Models estimate persistent state probabilities, together providing robust regime classification across bull, bear, and sideways environments.

Regime detection works across equities, FX, and multi-asset portfolios, applying Hidden Markov Models and Markov-switching methods to classify regimes and generate state probabilities regardless of the asset class.

Regime-switching models may be unreliable during transitional periods between states when probabilities are diffuse, or when structural breaks occur faster than the model adapts, producing uncertain classifications requiring additional confirmation.