Forex Correlation Matrix
Live Pearson correlation matrix across 10 major forex pairs. Toggle 7-day, 30-day, and 90-day windows. Color-coded so strong relationships pop visually.
Daily history is being prepared. The matrix will populate shortly.
For each pair the calculator builds a series of daily percentage returns over the selected window:
return[i] = (close[i] - close[i-1]) / close[i-1]
It then computes Pearson correlation between every pair of return series. Cells are coloured by the absolute correlation strength: deep green for strong positive, deep red for strong negative, near-neutral for weak relationships.
EUR/USD vs. GBP/USD typically prints +0.70 to +0.90 over 30 days because both are quoted against USD and pulled by the same dollar moves. EUR/USD vs. USD/CHF typically prints -0.80 to -0.95 because the euro and the franc trade as flight-to-safety pairs anchored to the same dollar leg, on opposite sides.
Practical use: if you are long EUR/USD and considering adding long GBP/USD, the matrix tells you whether you are diversifying or doubling down. At +0.85 you are essentially trading a bigger EUR/USD.
What is forex correlation?
Correlation measures how often two pairs move in the same direction. +1.00 means they move together perfectly, -1.00 means they move opposite, 0 means no relationship. EUR/USD and GBP/USD typically show strong positive correlation; EUR/USD and USD/CHF typically show strong negative correlation.
How is the matrix calculated?
For each pair we compute daily percentage returns over the selected window. The matrix then runs Pearson correlation between every pair of return series. The diagonal is always +1.00 (a series correlates perfectly with itself).
Why does this matter for risk?
Trading two highly-correlated pairs in the same direction doubles your effective exposure without doubling your account, because both positions tend to win or lose together. Trading negatively correlated pairs in the same direction often means you are just paying spread on a hedged book. The matrix lets you spot both situations.
Which window should I use?
Day traders care about short-window correlation – 7d captures recent regime. Swing traders watch 30d. Position-level analysis benefits from 90d, which smooths through one-off shocks. Correlations shift over time, especially around macro regime changes, so re-check before stacking trades.
How fresh is the data?
Daily closes are pulled from the AlphaScala price feed once per day, around 01:00 UTC. The matrix you see was computed against the most recent snapshot in the database.