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Currency Pair Correlations - Forex Trading

Understanding price relationships between various currency pairs allows to get a deeper insight on how to develop high probability forex trading strategies. Awareness of currency correlation can help to reduce risk, improve hedging and diversify trading instruments. In this article we will introduce you to forex trading using intermarket correlations.

Meaning of currency pairs correlation in Forex

Correlation is a statistical measure of the relationship between two trading assets. Currency correlation shows an extent to which two currency pairs have moved in the same, opposite, or totally random directions within a particular period.

Forex Correlation

Analysis of two assets relationships using a past statistical data has a predictive value, it can identify potential forex trading opportunities and manage your exposure to risk. Correlation is typically measured in decimal form on scale of -1 to +1 to give you a figure named a correlation coefficient.

  • A correlation of +1 shows that two currency pairs will move in the same direction 100% of the time. That is a perfect positive correlation. Correlation between EUR/USD and GBP/USD is an accurate example, as if EUR/USD is trading up, then GBP/USD is moving the same direction.
  • A correlation of -1 indicates that two currency pairs will move in the opposite direction 100% of the time. EUR/USD and USD/CHF have a perfect negative correlation, thus if EUR/USD moves upwards, then USD/CHF goes downwards.        
  • A correlation of zero takes place if relationship between currency pairs is totally random, which means they have no link at all.

Naturally, the stronger a positive or negative correlation, the greater a predictive value drawn from an analysis. Longer time frames used for a technical analysis shows more accurate information. Correlations over a 1 minute period have a little value, while monthly and yearly data provides the most reliable insight.

Impact of currency correlations on Forex trading

  • They can form a basis of a statistically high probability forex trading strategy.
  • They can illustrate the amount of risk you are exposed in your forex trading account. For example, if you have bought several currency pairs with a strong positive correlation then you are exposed greater directional risk.
  • You can avoid positions that effectively cancel each other out. EUR/USD and USD/CHF have a very strong negative correlation. If you have a directional bias, buying both EUR/USD and USD/CHF will counteract the moves in each pair.     
  • Understanding correlations can allow you to hedge or diversify your exposure to the forex  market.    
  • If you have a directional bias for a given currency, you can spread your risk using two strongly positive correlated pairs, in terms of diversification.
  • If you are looking to hedge a position (holding it with low risk of losses) you can take a position in a negatively correlated pair. For instance, if you initiate a long (buy) EUR/USD position and it starts moving against you, you can hedge the position by buying a negatively correlated pair such as USD/CHF.

Forex Trading strategies based on correlation

  • When two pairs are highly correlated, one can serve as a leading indicator to the price movement of the other. If you see a sharp move in one pair of two positively correlated pairs, you can anticipate a possible move in the other.

Correlation sharp move lagging

  • Correlation can be even more powerful forex tool for analysis in conjunction with another forex indicators.For instance, if one pair breaks out above or below a major technical level of support or resistance, the closely positively correlated pair has a high probability of following risk.
  • Price reversals. If you see two negatively correlated currency pairs and a significant upward price reversal in one pair takes place, then you can anticipate a potential downward reversal in the other pair.           
  • Non-directional arbitrage style strategy using currency correlations. In this forex strategy you wait for an abnormal divergence between two highly correlated currency pairs and buy one and sell the other, with the expectation that they will converge in price movement again.

Highly correlated currency pairs in Forex

Examples of strong positive correlations (Yearly time frame):

EUR/USD and GBP/USD (+ 0.89)

EUR/USD and AUD/USD (+ 0.81)

EUR/USD and EUR/CHF (+ 0.93)

AUD/USD and Gold (+ 0.75)

Examples of strong negative correlations (Yearly time frame):

EUR/USD and USD/CHF (- 0.85)

USD/CAD and AUD/USD (- 0.88)

AUD/NZD and NZD/SGD (- 0.78)

USD/JPY and Gold (- 0.78)

Commodities that are correlated with currencies

  • The Canadian Dollar and crude oil have a positive correlation, due to the fact that Canada is a major oil producer and exporter.
  • Similarly, the Australian Dollar and gold have a positive correlation, because Australia is a significant gold producer and exporter.

Positive correlation

  • Both gold and the Japanese Yen are viewed as safe havens in times of uncertainty and these two are also positively correlated.
  • Meanwhile, gold and the US dollar typically have a negative correlation. When the U.S. dollar starts to lose its value amid rising inflation, investors seek alternative stores of value such as gold.

Negative correlation

Currency correlations change in Forex

Be aware that currency correlations are constantly changing over time due to various economic and political factors. These often include diverging monetary policies, commodity prices, changes in Central Bank policy etc. Strong correlation is not guaranteed to be the same in the future what makes following the shift in correlations even more important. We recommend to check long-term correlation to get a better perspective.

You can take advantage of currency correlations forex trading opportunities, as they are an effective tool in developing high probability trading strategies. They can also help you in risk management, especially if you track the correlation coefficients over the daily, weekly, monthly and yearly timeframes.

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