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All trading involves risk. Ensure you understand those risks before trading.

Forex correlation: how do currencies align with other assets?

Article By: ,  Former Senior Financial Writer

Forex correlation: how do currencies align with other assets?

Currencies rarely move in isolation. Thanks to forex correlation, lots of pairs are closely aligned – and some even move predictably with assets outside of FX too. Let’s examine how currency pair correlation affects your trading, and whether you can use it to your advantage.

  1. What is forex correlation?
  2. What is the correlation coefficient?
  3. The most correlated FX pairs
  4. Commodity currency correlation
  5. Currency and stock market correlation
  6. Forex correlation trading tips

What is forex correlation?

Forex correlation is a measure of how much the movements of currency pairs are affected by each other. However, it can also describe the extent to which a forex pair’s movement is aligned with other markets, such as commodities or stocks.

FX pairs tend to be highly aligned with each other, as many of them share a currency. EUR/USD and GBP/USD, for example, both contain the US dollar. If the US dollar surges in value, both might fall.

There are two types of correlation to watch out for when trading forex: negative and positive.

  • Markets with negative correlation will experience inverse movements. If one goes up, the other should go down
  • Markets with positive correlation will experience similar movements. If one goes up, the other should go up too

    In our example above, EUR/USD and GBP/USD are positively correlated, as they’ll both experience the same outcome when USD moves. USD/JPY, on the other hand, would move in the opposite direction – so it is negatively correlated to both EUR/USD and GBP/USD.

 

What is the correlation coefficient?

The correlation coefficient is a formula that tells you how much two markets are aligned over a given period. It is calculated as a number between -1.00 and 1.00, and written as the symbol ρ.

  • The closer the coefficient is to 1.00, the more positively correlated the markets are
  • The closer the coefficient is to -1.00, the more negatively correlated the markets are
  • A figure at or near 0 means the markets aren’t correlated at all, or have an extremely weak alignment

Let’s continue our EUR/USD example to illustrate how this works in principle. In the table below, you can see how Eurodollar’s price action aligns with GBP/USD and USD/JPY over different periods.

 

EUR/USD correlation with other pairs

GBP/USD

USD/JPY

1 month

0.95

0.44

3 months

0.90

-0.42

6 months

0.66

-0.34

1 year

0.89

-0.55

As you can see, EUR/USD and GBP/USD are generally highly positively aligned. USD/JPY, on the other hand, tends to move mostly in the opposite direction – as it should, due to USD being the base currency in the pair instead of the quote.

Notice anything else in the table? Correlation can change drastically over time, with USD/JPY swinging from positive to negative in the first two rows. As you trade the FX markets, it’s always important to remember that just because markets have been correlated in the past doesn’t necessarily mean they will be forever.

 

Calculating the correlation coefficient

To calculate the correlation coefficient between two markets, you first need to work out both their covariance and their standard deviation. Then, you can input both into the following formula:

Ρ = cov(X,Y) / σXσY

If that sounds complex, then don’t worry. The City Index platform will automatically calculate the correlation coefficient between any two markets for you. Simply select ‘Indicators’ from a market’s chart, choose the correlation coefficient indicator and choose which market you’d like to compare.

Get started with your City Index account today – or try out trading with a free trading demo.

 

The most correlated FX pairs

The most correlated forex pairs tend to be those that not only share a currency, but also have close economic ties between the other currencies within the pair. This means that economic data and headlines will tend to affect each market in a similar way.

We’ve already encountered two FX markets that fit these criteria: EUR/USD and GBP/USD. As we saw in the table above, Eurodollar and cable tend to see very high levels of correlation. Why? Because not only do they both feature USD as the quote currency, but the UK and EU have a close economic relationship.

USD/JPY may also feature the US dollar, but its negative correlation to EUR/USD isn’t nearly as strong, peaking at -0.55. Let’s compare that to another pair with a negative correlation to Eurodollar, but this time with a quote that’s much closer economically to the euro: USD/CHF.

EUR/USD correlation with other pairs

USD/JPY

USD/CHF

1 month

0.44

-1.00

3 months

-0.42

-0.96

6 months

-0.34

-0.90

1 year

-0.55

-0.97

Here, the inverse relation is much clearer, with USD/CHF seeing a perfect negative correlation with EUR/USD due to the close ties between the European Union and Switzerland.

 

How to trade forex correlation pairs

To start finding and trading correlated forex pairs today, follow these steps:

  1. Open your City Index account, or log in if you already have one
  2. Add some funds so you can start trading instantly
  3. Search for correlated markets in our award-winning web platform or mobile trading app
  4. Open your position

Or if you don’t feel ready to commit real capital just yet, you can open a City Index demoinstead. These come with virtual funds so you can find and trade correlated markets with zero risk.

 

Commodity currency correlation

Currencies aren’t only correlated with each other, though. They can also align with other asset classes entirely: and most often, they do so with commodities. This occurs through ‘commodity currencies’ – which are tied to regions dependent on a particular raw material for their economic growth.

Canada, for example, is a major exporter of oil. When oil prices are high, Canada makes a lot of profit from its exports, and its economy booms – which will usually play out across CAD. This results in a strong inverse relationship between oil prices and USD/CAD.

When oil prices fall, the Canadian dollar falls too, which causes USD/CAD to rise. If oil rises, CAD rises too – and its pair with USD falls. Markets with the Canadian dollar as the base currency will have a positive correlation instead.

 

The US dollar and gold

USD, meanwhile, has a strong inverse relationship to gold, but not because the US economy is dependent on exporting the precious metal. Instead, XAU and the US dollar move against each other because gold is priced in USD.

When the dollar is strong against other currencies, it means it takes more USD to buy the same amount of bullion, which pushes gold’s price down. When the dollar is weak, the opposite occurs. You can buy more gold for your dollar, which drives up demand and sees gold’s price rise.

You can see this relationship playing out in the chart below, which compares XAU/USD against the dollar index:

It isn’t just gold, either. Most commodities are priced in dollars, so will have some form of inverse relationship with USD.

 

Currency and stock market correlation

Currencies can also be related to the stock market, but the relationships can be complex and play out in different ways depending on the stock you’re looking at. There are, however, some clearly correlated markets to be found.

Pound sterling, for example, often sees a strong negative correlation to the FTSE 100. This arises because most of the companies on the FTSE – such as GlaxoSmithKline, HSBC and Shell – have a strong international outlook. When GBP is weak, this increases their bottom line because exports in foreign currency are worth more.

We saw this relationship play out after the 2016 Brexit vote, when the pound dropped to new lows and the FTSE 100 rallied. The more domestically focused FTSE 250, on the hand, sunk.

A similar relationship plays out between USD and US stocks. If a company makes most of its revenue overseas, then a strong US dollar is bad for business – which is why central banks sometimes step in when currencies run too hot. Companies that focus mostly on the US, however, will often struggle due to the slowing economy that often accompanies a weak US dollar.

When trading the relationship between FX and stocks, then, the key is to take everything on a case-by-case basis. Research the companies you’re considering trading and evaluate how their business might be affected by fluctuating exchange rates.#

 

Forex correlation trading tips

There are several ways you can use correlated markets in your trading strategy. The most common, though, is to avoid markets with strong relationships when you’re attempting to diversify your portfolio.

If you have open positions in the same direction on two highly correlated markets, then a loss in one will probably see you lose in the other one too, doubling your risk. So many traders try to stick to markets that have little relationship with one another.

You can also use negatively correlated markets to proactively manage risk by hedging. Say, for example, that you have a long EUR/USD position that you’re worried is about to incur a loss. Instead of closing the trade, you could buy a negatively correlated market such as USD/CHF. Then, losses in your Eurodollar position may be offset by gains in the Swissie trade.

 

Forex correlation trading tips

  • Remember, correlations aren’t set forever. Markets that are firmly correlated most of the time may show periods of weakness. This makes it important to look at both shorter-term and longer-term correlations
  • When placing a trade, consider whether the markets are currently correlated, whether one market leads another and whether the price is diverging. For instance, if one market is in a strong trend and the other is rangebound, it may be worth waiting for a period of sustained correlation
  • AUD/USD is historically positively correlated with gold, as Australia is a major gold producer. However, to trade this relationship you’ll need to learn the fundamental factors impacting gold production schedules and demand patterns

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