Currency Correlation: Which Forex Pairs Move Together and How to Use It

Currency correlation measures how closely two forex pairs move in the same or opposite direction. It matters because two trades that look separate on your screen can be the same bet twice, doubling your risk without you noticing. This guide explains how currency correlation works, which pairs usually move together or apart and why, how to calculate the correlation coefficient yourself, and how to use it to size, hedge and confirm trades.

What Is Currency Correlation in Forex?

Currency correlation is the statistical relationship between the price movements of two currency pairs, expressed as a coefficient between −1 and +1. A coefficient of +1 means the pairs move in the same direction every time. A coefficient of −1 means they move in exactly opposite directions. A coefficient near 0 means their movements are unrelated.

Forex traders borrow the measure directly from statistics, where correlation describes how linearly related two variables are. The most common version is the Pearson correlation coefficient, which is what most correlation tables and indicators show.

One point from statistics matters a great deal in trading: correlation does not mean one pair causes the other to move. EURUSD and GBPUSD tend to rise together because both are priced against the US dollar, not because one drives the other. When the shared driver changes, the correlation can change too.

How to Read the Currency Correlation Coefficient

The currency correlation coefficient tells you both the direction and the strength of the relationship between two pairs. Positive values mean the pairs tend to move the same way; negative values mean they tend to move opposite ways; the closer the number is to +1 or −1, the stronger the link.

These bands are a working guide, not a law. A coefficient of +0.75 calculated over the last month says more about current risk than a +0.90 calculated over the last five years.

Which Forex Pairs Move Together? Common Positive Correlations

The forex pairs that usually move together are those that share the same quote currency and whose base currencies are tied by economics or sentiment. In forex trading, the classic examples involve pairs quoted against the US dollar.

EURUSD and GBPUSD typically show a strong positive correlation. Both are priced in dollars, so any broad dollar move pushes both pairs the same way, and the eurozone and UK economies are closely linked. When the dollar weakens after a soft US data release, both pairs tend to rise together.

AUDUSD and NZDUSD are often among the most tightly correlated pairs in the market. Australia and New Zealand are neighbouring economies with similar export profiles and strong trade ties with Asia, and both currencies react in a similar way to global risk appetite.

EURUSD and AUDUSD are also usually positively correlated, though less strongly. They share the dollar as quote currency, but the euro and the Australian dollar respond to very different domestic drivers, so their link loosens whenever those drivers diverge.

What Correlation Means for Cross Pairs Such as EURGBP

A cross pair such as EURGBP is effectively the ratio of two dollar pairs, EURUSD divided by GBPUSD. With EURUSD at 1.1600 and GBPUSD at 1.3400, EURGBP is about 1.1600 ÷ 1.3400 = 0.8657.

When EURUSD and GBPUSD are tightly correlated, they rise and fall by similar percentages, so their ratio barely changes and EURGBP trades in a narrow range. When the correlation weakens, for example after a surprise from the Bank of England or the European Central Bank, EURGBP starts to trend. Watching the EURUSD and GBPUSD correlation is a quick way to judge whether EURGBP is likely to stay quiet or break out.

Which Forex Pairs Move in Opposite Directions?

Forex pairs tend to move in opposite directions when the same currency sits on opposite sides of the two quotes. The clearest example is EURUSD and USDCHF: the dollar is the quote currency in the first pair and the base currency in the second.

When the dollar strengthens, EURUSD falls and USDCHF rises. The two pairs have historically shown a strong negative correlation, helped by the close economic ties between the eurozone and Switzerland. GBPUSD and USDCHF, and EURUSD and USDJPY, follow the same structural pattern, though the second relationship is usually weaker because the yen has its own drivers.

Some traders try to hedge by holding opposite positions in negatively correlated pairs, such as long EURUSD and long USDCHF. Whether you can hold offsetting positions at all depends on your account type and platform settings, so check the conditions a trusted forex broker states for each account before relying on that approach. The hedge is also never perfect, as the risk section below shows.

Why Currency Pairs Are Correlated

Currency pairs are correlated for four main reasons: a shared currency, linked economies, common reactions to global risk, and shared exposure to commodities. Most strong correlations involve more than one of these at the same time.

A shared currency is the most mechanical reason. Any pair with the dollar in it carries part of every dollar move, which is why so many dollar pairs correlate with each other. Linked economies add to it: trade between the eurozone and the UK, or between Australia and New Zealand, means their currencies respond to similar news.

Risk sentiment is the third driver. In risk-on periods, when investors buy equities and higher-yielding assets, currencies such as the Australian and New Zealand dollars tend to rise together, while the yen and the Swiss franc tend to weaken. In risk-off periods the pattern reverses, which makes the yen and franc behave alike.

Commodity Currency Correlations: CAD and Oil, AUD and Gold

Commodity currencies tend to correlate with the prices of the commodities their economies export. The Canadian dollar is linked to crude oil, and the Australian dollar has historically shown a link with gold and industrial metals.

Because the Canadian dollar is the quote currency in USDCAD, a rising oil price that strengthens the Canadian dollar pushes USDCAD down. That makes USDCAD and oil negatively correlated for much of the time. Anyone combining forex positions with commodities trading on oil or gold should treat those positions as partly overlapping.

The Australian dollar's link to gold reflects Australia's role as a major gold producer, and AUDUSD and gold have often moved in the same direction. The relationship is looser than the textbook version suggests, however, because iron ore, China's economy and interest rate expectations often matter more to the Australian dollar than gold does.

How to Calculate Currency Correlation: A Worked Example

You calculate currency correlation by comparing the percentage changes of two pairs over the same periods and applying the Pearson formula. A spreadsheet's CORREL function does the arithmetic, but working one example by hand shows what the number means.

Here are five days of percentage changes for EURUSD and GBPUSD:

The calculation runs in three steps:

1. Find each pair's average change. EURUSD averages 0.00% and GBPUSD averages +0.02%.

2. For each day, subtract the average from each pair's change, multiply the two results together, and add up the five products. The total is 0.775.

3. Square each pair's daily deviations and add them up: 0.625 for EURUSD and 0.983 for GBPUSD. Divide 0.775 by the square root of 0.625 × 0.983, which is about 0.784.

The result is 0.775 ÷ 0.784 = +0.99, a very strong positive correlation. In practice, five days is far too short a sample; traders usually use 20 to 100 periods of daily or hourly data. You can export price history from any MT5 broker platform by opening the Symbols window with Ctrl+U, choosing the Bars tab, requesting the data and exporting it to a file for a spreadsheet.

How Currency Correlation Changes Over Time

Currency correlation is not fixed; it changes as the forces behind it change. A pair of currencies that moved tightly together for a year can drift apart within weeks when one central bank changes direction or a country faces its own political or economic shock.

That is why traders look at correlation over more than one window. A correlation calculated over the last 20 trading days shows the current relationship, while one calculated over the last 250 days shows the longer-term norm. When the two disagree sharply, the relationship is changing, and positions built on the old pattern need a second look.

Correlations also tend to rise during market stress. In a sharp risk-off move, many pairs move in step with the dollar or the yen at once, so a portfolio that looked diversified in calm markets can behave like one large position in a crisis.

Using Currency Correlation to Manage Risk

Currency correlation is most useful for spotting hidden concentration of risk across your open positions. Two trades on strongly correlated pairs in the same direction behave like one larger trade, so their combined risk is close to the sum of both, not the average.

Here is how that plays out. On a $10,000 account with a 1% risk rule, you buy 0.4 lots of EURUSD with a 25-pip stop, risking $100. You also buy 0.4 lots of GBPUSD with a 25-pip stop, risking another $100. Each trade follows the rule, but if the dollar rallies hard, both stops are likely to be hit together, and you lose $200, or 2%, on what was really one idea: selling the dollar.

The fix is to treat strongly correlated positions as a single position for risk purposes. Either split your normal risk between them, for example 0.2 lots on each pair, or pick the stronger setup and skip the other.

Why Negatively Correlated Hedges Are Never Exact

A hedge using negatively correlated pairs reduces risk but does not remove it. Suppose you hold 1 lot long EURUSD and 1 lot long USDCHF with USDCHF at 0.8000, and the dollar strengthens so that both pairs move 50 pips.

EURUSD loses 50 × $10 = $500. USDCHF gains 50 pips at 10 francs per pip, which is 500 francs, worth about $625 at 0.8000. The net is a gain of $125, not zero.

The mismatch comes from different pip values and from the correlation being less than −1 in practice. You also pay two spreads and carry two sets of overnight swap charges, so a correlation hedge has a running cost even when it works as intended.

Using Correlation to Confirm Trade Ideas

Currency correlation can also confirm or question a trade idea. If you want to buy EURUSD because you expect the dollar to weaken, check whether GBPUSD and AUDUSD are also rising. A move that shows up across several dollar pairs suggests broad dollar weakness rather than euro-specific news.

When the pairs disagree, that tells you something too. If EURUSD is rising while GBPUSD and AUDUSD are falling, the move is probably about the euro, not the dollar. That changes which news to watch and how much confidence to place in the trade.

Common Currency Correlation Mistakes

The most common currency correlation mistake is opening several trades on strongly correlated pairs and counting them as separate bets. Three longs on EURUSD, GBPUSD and AUDUSD are largely one short position on the dollar, with three times the intended risk.

The second mistake is relying on an old correlation table. A coefficient published years ago may bear little relation to how the pairs behave today, so check recent data before acting on any relationship.

The third mistake is assuming that a negatively correlated hedge locks in a result. Different pip values, imperfect correlation, double spreads and overnight swaps all leave a hedged position exposed to some gain or loss.

Putting Currency Correlation to Work

Currency correlation shows which forex pairs move together and which move apart, measured by a coefficient from −1 to +1. Pairs sharing the dollar on the same side, such as EURUSD and GBPUSD, usually move together; pairs with the dollar on opposite sides, such as EURUSD and USDCHF, usually move apart.

Use correlation mainly to see your true exposure. Treat strongly correlated positions as one trade for risk purposes, recheck correlations over recent data rather than trusting old tables, and remember that relationships shift when the economic forces behind them change.