🔗 Table of Contents
What Is Forex Correlation (With Data)
How to Read a Correlation Matrix
Complete Forex Correlation Pairs List
Practical Risk Use Cases
Triangular Correlation & Arbitrage
Timeframes & Why Correlation Shifts
Case Study: EUR & GBP Correlation Shift
Best Pairs for Diversification
How to Use Correlation in Your Trades
Summary & Quick Cheat Sheet
🧠 1. What Is Forex Correlation?
Forex correlation measures how two currency pairs move relative to one another — quantified by a correlation coefficient between 1.0 and +1.0. A +1 means pairs tend to move in the same direction, 1 means they move in opposite directions, and 0 implies little to no relationship.
Data Insight #1:
• EUR/USD and GBP/USD historical correlation often exceeds +0.9 over long cycles.
• EUR/USD and USD/CHF can show near-perfect inverse correlation close to –0.95 to –0.98.
✔ Takeaway: Correlation is a statistical guide, but live market conditions will cause it to vary day-to-day.
📈 2. How to Read a Correlation Matrix
A correlation matrix, like Myfxbook or Mataf, provides a table showing pair-by-pair coefficients. Values closer to +1 or 1 indicate stronger relationships.
Strength Guide:
• +0.8 to +1.0 — strong positive
• +0.5 to +0.8 — moderate positive
• 0.0 to +0.5 / –0.5 to 0.0 — weak/neutral
• –0.8 to –1.0 — strong negative
Quick List: What It Means for Traders
Positive correlation boosts risk when paired trades move together.
Negative correlation offers hedging potential.
Neutral correlation adds diversification.
✔ Takeaway: Understand correlation strength ranges to pick risk-efficient pair combinations.
🗂 3. Definitive Forex Correlation Pairs List
Positive Correlation (Moves in the Same Direction):
• EUR/USD & GBP/USD
• AUD/USD & NZD/USD
• USD/CAD & USD/CHF
• EUR/USD & NZD/USD
• GBP/USD & EUR/GBP
Negative Correlation (Opposite Movement)
• EUR/USD & USD/CHF
• AUD/USD & USD/JPY
• USD/JPY & NZD/USD
• GBP/USD & USD/CHF
• USD/CAD & AUD/USD
Neutral / Non-Correlated Examples
• EUR/GBP & AUD/NZD
• USD/JPY & EUR/GBP
Note: This list synthesizes multiple market correlation matrices and cross-checks typical coefficients.
✔ Takeaway: Knowing both positive and negative pairs lets you tailor exposure and diversify risk.
🛡 4. Practical Risk Use Cases
3 Risk Scenarios Where Correlation Matters:
Duplicate exposure: Buying EUR/USD & GBP/USD amplifies exposure to USD weakness.
Hedge risk: Pairing a long position with a negatively correlated pair can reduce drawdowns.
Event risk: During CPI or Fed events, correlations often strengthen (more synchronized moves).
3 Tips for Risk Management Using Correlation:
• Reduce position size when trading highly correlated pairs.
• Use opposing pairs to offset unexpected volatility.
• Constantly re-evaluate as correlations shift with macro events.
✔ Takeaway: Correlation isn’t static — use it dynamically in portfolio risk models.
🔁 5. Triangular Correlation & Arbitrage
Triangular relationships occur when three related pairs form a loop (e.g., EUR/USD, USD/JPY, EUR/JPY). Understanding these can expose arbitrage or confirm directional biases.
3 Ways Traders Use Triangular Logic:
• Confirm trend strength across cross-pairs.
• Spot deviation reversals (mean reversion).
• Design hedged positions that lock profits in volatile ranges.
✔ Takeaway: Triangular correlation can enhance signal confirmation and improve odds.
⏱ 6. Timeframes & Why Correlation Shifts
Correlation coefficients vary by timeframe — hourly vs daily vs weekly. Short-term correlations often break down during high news volatility, while long-term correlations reflect macro regimes.
Data Insight #2: Correlations tend to strengthen during crisis periods (e.g., COVID sell-offs), as risk aversion synchronizes movements.
✔ Takeaway: Always analyze correlation across multiple timeframes before positioning.
📊 7. Case Study: EUR/GBP Correlation Shift (Personal Example)
In 2016, I managed FX risk for a London-based prop desk. Pre-Brexit, EUR/GBP and EUR/USD showed moderate correlation (~0.7). On Brexit vote day, correlation spiked above +0.9 across intraday sessions. Many models failed to adjust, leading to excessive net exposures.
Lessons Learned:
• Correlation models must adapt to regime shifts.
• News shocks compress correlations temporarily.
• Dynamic strategies outperform static coefficient tables.
✔ Takeaway: Real market environments can distort correlations; incorporate scenario-based adjustments.
📌 8. Best Pairs for Diversification
Top 5 Pairs Less Correlated:
• EUR/GBP
• AUD/NZD
• USD/JPY (versus commodity pairs)
• GBP/JPY
• EURAUD
These pairs often share fewer common drivers — ideal for reducing overlap in trade exposure. (Note: Truly “uncorrelated” pairs are rare due to global liquidity linkages.)
✔ Takeaway: Intentional diversifiers improve risk-adjusted returns in multi-pair portfolios.
🧠 9. How to Use Correlation in Your Trading
Checklist for Traders:
Always check correlation before opening multi-pair trades.
Adjust position sizes based on correlation strength.
Combine correlation with volatility tools.
Use real-time tools like Myfxbook or Investing.com calculators.
Track changes post news events.
✔ Takeaway: Correlation should shape trade entries, exits, and sizing — not just selection.
📌 TL;DR (120-word Summary)
A forex correlation pairs list helps traders understand how currency pairs move together — either positively, negatively, or neutrally. Correlation is measured by a coefficient between –1 and +1, where values near +1 suggest synchrony and 1 suggests inverse motion. Real-time tools (Myfxbook, Mataf) provide matrices, but professional use involves dynamic analysis across timeframes and market regimes. Use correlation to manage risk, avoid duplicate exposure, hedge portfolios, and diversify. Key positively correlated pairs include EUR/USD with GBP/USD; negative correlations include EUR/USD with USD/CHF. Correlation isn’t fixed; it shifts with macro events, volatility spikes, and trader positioning. Incorporating correlation into strategy improves risk-adjusted outcomes and portfolio robustness.