What is a correlation coefficient
A correlation coefficient is a statistic that measures how closely the movements of two series follow each other. It runs on a fixed scale from perfect negative to perfect positive.
- Positive end of the scale: the series move in the same direction.
- Negative end of the scale: the series move in opposite directions.
- Middle of the scale: there is no consistent linear link.
In trading, correlation is used to see whether positions in different instruments add to the same risk or offset each other.
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Formal definition
The usual measure is the Pearson coefficient. It is the covariance of the two series divided by the product of their standard deviations. Dividing by the standard deviations makes the result independent of units, so the measure stays on the same fixed scale. The same formula works for a currency pair, a stock index or gold.
Traders normally calculate it on returns, meaning percentage or log changes per bar, not on raw prices. Two price series that both trend upward can show a high coefficient even when their day-to-day moves are unrelated.
Worked example (hypothetical)
Take daily returns of EUR/USD (Fiber) and GBP/USD (Cable) over the same recent period. Both pairs are quoted against the US dollar, so a broad dollar move pushes them in the same direction. In this hypothetical case, the coefficient comes out strongly positive, near the top of the scale.
Now take EUR/USD and USD/CHF. Here the dollar is the quote currency in the first pair and the base currency in the second. A dollar rally lowers the first pair and raises the second. In this hypothetical case, the coefficient comes out strongly negative.
For a trader, this means that a long position in both EUR/USD and GBP/USD is largely the same bet on the dollar. The combined exposure is larger than each position looks on its own. See currency pairs for how base and quote currencies work.
Where you see the term
- Correlation matrices on analytics sites, which show currency correlation for many pairs over chosen periods.
- Charting platforms, where some traders add a custom correlation indicator to MetaTrader 5 or similar software.
- Market news and research, for example comments that the link between the dollar and gold has weakened, or that stock indices such as NAS100 and US100 move almost as one.
- Portfolio and risk reports, next to beta and volatility.
Edge cases and limits
- Unstable over time. Correlations change. During stress they often move toward the extremes, as described in financial contagion and flight to quality.
- Window length matters. A short window reacts fast but is noisy. A long window is smoother but slower to show change.
- Only linear links. A coefficient near the middle does not prove the series are independent.
- Outliers. A single extreme day can distort the result. Rank-based measures such as Spearman are less sensitive to this, which matters with fat tails.
- Not causation. Two series can move together because a third factor drives both.
Correlation describes the past. It does not predict the future. Leveraged forex and CFD positions that turn out to be correlated can lose money together and fast, so read risk management before relying on any hedge.
Related terms
Beta · Alpha · Currency risk · Dollar smile theory · Trading glossary
Frequent questions
What does correlation mean in trading?
It shows how closely two instruments have moved together in the past. Traders use it to see whether their positions share the same risk.
Is a negative correlation a hedge?
It can partly offset risk, but correlations shift. A hedge based on past correlation can fail exactly when markets are under stress.
Should I use prices or returns?
Use returns. Correlation calculated on raw price levels often shows links that are not really there.
Does high correlation mean one market causes the other?
No. It only measures co-movement. A shared driver, such as the US dollar, is a common reason two markets move together.