Correlation Regime Switcher

Correlation Regime Switcher

import pandas as pd
import numpy as np

class CorrelationRegimeSwitcher:

    REGIME_STRATEGIES = {
        "normal_correlation": {
            "description": "Correlations at historical norms",
            "strategies": ["trend_following", "carry_trade", "mean_reversion_pairs"],
            "risk_level": "NORMAL",
        },
        "correlation_breakdown": {
            "description": "Historical correlations breaking down",
            "strategies": ["single_pair_momentum", "volatility_selling"],
            "risk_level": "ELEVATED — reduce correlated positions",
        },
        "correlation_spike": {
            "description": "All assets moving together (crisis mode)",
            "strategies": ["safe_haven_only", "volatility_buying", "cash"],
            "risk_level": "HIGH — correlation=1 means no diversification benefit",
        },
        "decorrelation": {
            "description": "Assets becoming uncorrelated — dispersion rising",
            "strategies": ["pairs_trading", "relative_value", "basket_trades"],
            "risk_level": "OPPORTUNITY — dispersion creates relative value trades",
        },
    }

    @staticmethod
    def detect_regime(correlation_matrix: pd.DataFrame, historical_avg_corr: float) -> dict:
        """Classify current correlation regime."""
        upper_tri = correlation_matrix.values[np.triu_indices_from(correlation_matrix.values, k=1)]
        current_avg = np.mean(np.abs(upper_tri))
        deviation = current_avg - abs(historical_avg_corr)

        if current_avg > 0.8:
            regime = "correlation_spike"
        elif deviation > 0.15:
            regime = "correlation_spike"
        elif deviation  dict:
        """Detect regime transitions from rolling correlation data."""
        recent = rolling_corr.tail(window)
        prior = rolling_corr.iloc[-(window*2):-window]
        change = recent.mean() - prior.mean()
        return {
            "transition_detected": abs(change) > 0.2,
            "direction": "CONVERGING" if change > 0.2 else "DIVERGING" if change  0.2 else "Hold current strategies",
        }

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: mahmoud20138
• Source: mahmoud20138/Tradecraft
• License: MIT

Install and usage instructions live in the source repository linked above.