Intermarket Correlation Trading

Analyzing relationships between different markets to gain trading edge. Markets are connected through capital flows, economic relationships, and investor behavior. Trading opportunities arise from divergences and lead-lag relationships.

DAX (German index): 0.85-0.95 correlation. CAC 40 (France): ~0.88. S&P 500: 0.75-0.90. Other European indices highly correlated due to similar trading hours and economic exposure.

Trading the difference (spread) between two correlated markets. When spread is extreme (z-score beyond ±2), enter expecting reversion to mean. Exit when spread normalizes.

Compare performance of correlated markets. If FTSE down 1% and DAX up 0.5% on same day (1.5% divergence), that's significant for highly correlated markets. Use z-score for precise measurement.

Timezone allows monitoring all major sessions: Asian (morning), European (afternoon/evening), US (evening/night). Can see how correlations play out across sessions and trade handoff opportunities.

Correlation calculated over moving window (typically 20 days). Updates daily. Shows how relationship changes over time. Critical for monitoring - if correlation dropping, intermarket trades riskier.

Often inverse relationship (-0.30 to -0.60). FTSE 100 has 70%+ overseas revenues. Weaker GBP makes those earnings worth more. Can trade divergences when GBP and FTSE move same direction unexpectedly.

S&P 500 often leads FTSE during US session. Watch S&P move, trade FTSE expecting follow-through. Entry: When lead market moves significantly and lag market hasn't caught up. Short time window.

During crises (2008, 2020): Correlations spike to ~1.0. Brexit: FTSE-European correlations disrupted. Major news: Country-specific events change relationships. Monitor daily and exit if correlation drops significantly.

Conservative: 0.75-1.0% risk per trade. Smaller than directional trades due to correlation uncertainty. Use correlation-adjusted sizing: Lower correlation = Smaller size.

Long-term equilibrium relationship. Two series share equilibrium - may wander individually but spread is stationary. Test with Engle-Granger or Johansen methods. Stronger foundation than correlation for pairs trading.

From cointegration regression: β coefficient. Determines position sizing ratio. Example: β = 0.45 means long 1 FTSE, short 0.45 DAX equivalent. Creates market-neutral position profiting from spread reversion.

Common drivers: Risk-on/risk-off sentiment, USD strength, commodity prices, interest rates. Decompose returns into factor and residual. Trade residual divergences after removing factor effects for cleaner signals.

Combine: Spread trades (30%), lead-lag (25%), currency-equity (20%), cross-asset (15%), other (10%). Total intermarket: 10-20% of trading capital. Diversify across relationship types. Monitor net exposures.

Extend beyond equities: Bonds (yields signal risk appetite), commodities (oil, gold as indicators), currencies. Gold rising = Risk-off warning for equities. Yield spike = Equity caution. Multiple asset classes provide early signals.