Regime Detection System

Check ADX for trend (>25 trending, <20 ranging). Check volatility (VIX or historical vol). Combine: e.g., 'Trending + High Vol'. Also look at MA slope for direction. Start simple with these basic indicators.

Major regimes can last months to years. Minor regime shifts happen more frequently. Volatility regimes can change quickly (calm to crisis in days). Don't over-react to short-term fluctuations - look for confirmed, persistent changes.

It depends on your strategies. If you only have trend-following strategies, consider reducing activity in ranging markets. Better to wait for your regime than force trades in unfavorable conditions.

Yes. The same principles apply to stocks, forex, commodities, crypto. The specific thresholds may differ (crypto is more volatile than bonds), but the framework of trend + volatility regimes is universal.

Price vs 50-day MA (above = bullish, below = bearish) + VIX level (>25 = high vol, <15 = low vol). This gives you a basic 4-regime framework with minimal complexity.

Watch for: ADX declining from high levels (trend ending), volatility expanding from low levels (calm ending), price breaking established ranges (trend starting), divergences between price and momentum. These are early warnings, not certainties.

Trending: favor momentum, trend following. Ranging: favor mean reversion, range trading. High vol: reduce size, widen stops. Low vol: can use tighter stops. Have a strategy allocation table for each regime.

Use consensus. If ADX says trending but MA slope is flat, it's unclear - be cautious. More indicators agreeing = higher confidence. When signals conflict, reduce position sizes or wait for clarity.

Require confirmation: don't switch on one day's reading. Use smoothing or require 3-5 consecutive days in new regime. Transition gradually rather than all-at-once. Accept that some false signals are inevitable.

Absolutely. TSX might be ranging while energy is trending up due to oil prices. Analyze sector regimes separately. This creates opportunities - find sectors in favorable regimes even if the overall market isn't.

Use hmmlearn (Python) or depmixS4 (R). Input return series. Specify number of states (2-4 typical). Fit model with Baum-Welch. Use Viterbi for most likely state sequence or forward-backward for state probabilities. Validate out-of-sample.

Must pre-specify number of regimes. Regime definitions may not match intuition. Parameters can be unstable with short data. Transitions are assumed Markov (memoryless) which may not hold. Models are backward-looking - identifying current regime, not predicting next.

Ensemble approach: get regime from rules-based, HMM, and ML model. Vote or average probabilities. When methods agree, high confidence. When they disagree, lower confidence and reduce exposure. Each method has different strengths.

When regime is clear (high confidence), allocate strongly to regime-appropriate strategies. When uncertain, allocate more evenly or increase cash. Use probability-weighted allocation: Alloc = P(regime) × regime_optimal_alloc.

Retrain periodically (quarterly or annually) as market dynamics evolve. Monitor model performance - if accuracy degrades, retrain sooner. Use walk-forward validation continuously. Keep backup rules-based system if model fails.