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Currency Correlation What is it? How do I use?
by Martin ·
In forex currencies are quoted in pairs (euro-dollar, pound, yen, etc) and the contribution of each pair is not completely independent from the rest but there is a correlation, interdependence. Understanding the correlation between currencies may cause you to take advantage of this feature as part of your portfolio.
Currency Correlation
Correlation in financial terms is the measure of the relationship between two instruments, in this case currency pairs. It is usually expressed using the correlation coefficient, a figure that varies between -1 and +1. A correlation of +1 indicates that two currency pairs move in the same direction 100% of the time. On the other hand, a correlation coefficient of -1 indicates just the opposite, that the two currency pairs under study moves in the opposite direction 100% of the time. Keep in mind that a correlation of zero indicates that the relationship between currency pairs is completely random.
Why is there this interdependence of currency pairs? To take an obvious example is operating suppose EUR / JPY (pound sterling against the Japanese yen). This pair is within the so-called cross (currency pairs that do not include the USD). The EUR / JPY may be considered as a derivative of EUR / USD and USD / JPY as the EUR / JPY must be correlated with either of these two, or rather both. Of course, the correlation between currency pairs goes far beyond this simple fact and may be a result many mechanisms and situations. For example, a geo-political environment similar two currencies can be given to making a positive correlation with the USD peers have some correlation.
Calculating the correlation coefficient between currency pairs
The correlation coefficient is not static but changes over time due to the many factors affecting each currency. The calculation of the coefficient of correlation between currency pairs is quite tedious. The formula is:
ρ xy = cov (X, Y) / σ x σ and
Where cov is the covariance between X and Y and σ is the standard deviation.
Best to save all the work is to use Excel and function correlated. For example, if you’re going to calculate the correlation between EUR / USD and GBP / USD for the last 20 days. Open Excel and put in a column the closing prices of the last 20 days of EUR / USD, do the same in another column for GBP / USD. At the end of a column type = CORREL (now selects all cells in the first column, the box will now show the formula = CORREL (A1: A20 and put a comma at the end. Select the cells in the other column. Closed the formula should be something like = CORREL (A1: A20, B1: B20) and hit enter. The result is the correlation between EUR / USD and GBP / USD from the previous 20 days.
The most representative data correlation are related to 1 year, 6 months, 3 months and 1 is not very useful mes.Y correlation data update every day, do it every week or even only every month is more than enough. It is also important to note each month the correlation coefficient obtained in order to have a vision of long-term correlation, for example the correlation of the last month is very strong but we have the data from month to month for 1 year and the average gives low correlation, one can conclude that this strong correlation is timely and is not consistent with the historical correlation of the pairs under study.
Interpretation of the correlation coefficient
The correlation coefficient ranges from +1 to -1 and you can sometimes see it converted to% (-100% to +100%). His performance can be summarized as the following:
Maximum correlation: this is the value of +1, indicating that the two currency pairs move in the same direction as long as the same speed.
Maximum opposite correlation: the pairs are always moving in the opposite direction and is indicated by the value -1.
Positive values close to +1: Positive values near +1 indicate the two pairs generally move in the same direction most of the time and a similar speed. In general, a coefficient of correlation greater than or equal to +0.85 is considered a strong correlation.
Negative values close to -1: -1 cerana Negative values indicate that the two pairs moving in the opposite direction most of the time. In general, a correlation less than -0.85 indicates a strong opposite correlation.
Values between 0.5 to 0.85 are both positive and negative correlation of mean force.
Values of pr correlation coefficient below 0.5 is considered a weak correlation, the couple move in the same direction at speeds quite different and not always.
Correlation coefficient equal to zero indicates total independence, the two studied currency pairs will move in the opposite direction or completely random and unpredictable.
Using the correlation between currency pairs
Use as a trading strategy
The wider use of the correlation between currencies is the search for trading opportunities where there is a deviation between the correlation in the short term and long-term correlation.
To use this strategy and find the opportunity of trading you should note the correlation between two currency pairs in recent days and compare the data with the correlation obtained from a longer period, for example one year. When the difference between the two figures is high have a chance of trading. Here is an example to explain how and why:
Suppose that you are trader in two currency pairs, A and B, with a correlation coefficient of 0.98 for the last year. This means that both pairs moving in the same direction almost always have a strong positive correlation. If A is moved up, B also moves upward almost at the same speed. Suddenly you realize that the correlation with data of one week is $ 0.10. Given that historically the two pairs has a correlation of 0.98 we can deduce that the correlation will return to that value or values close. We must identify which pair of the two has slowed and what is the direction in which both have been moving in the long term to enter this address in the pair is moving slower.
Another fairly common strategy is also based on the deviation between pairs identi strongly correlated and operate your crossing. For example we can look at the correlation between EUR / USD and USD / CHF, historically have a very strong negative correlation, almost 100%. Where there is a sudden drop in correlation between pairs of trading we have opportunities in EUR / CHF interesting.
Use to reduce market exposure
To determine the correlation between two currency pairs can help us in making certain decisions. For example, it is widely known that the pair EUR / USDy USD / CHF have a strong negative correlation, if the EUR / USD lower, the USD / CHF also drop almost 100% of the time. Buy EUR / USD and selling USD / CHF is virtually like having no position in the market. Similarly, hold positions in two pairs with strong positive correlation is almost double the size of one of the positions, eg go long on EUR / USD and AUD / USD.
As you can see the data of the correlation can help us learn more we’re doing with our operations.
Use as diversification
In the previous paragraph we saw how to maintain a position in the same direction in two pairs with strong positive correlation is almost double the position in one of the pairs. However, a strong positive correlation but imperfect, not over 0.85, may serve to diversify our strategy in order to reduce risk. For example, we are clear that the USD is weak so we decided to buy EUR / USD. To diversify our strategy of weakening U.S. dollar can buy half in EUR / USD and the other half in AUD / USD.
Use as cover positions
When two currency pairs have a strong negative correlation can open positions in both pairs by way of coverage. For example, USD / CHF and EUR / USD has an almost perfect negative correlation. The value of the pip on EUR / USD is $ 10 per lot operated while USD / CHF is $ 8.34. If we are to go long on EUR / USD, we can cover our selling in USD / CHF. The lower value of pip in USD / CHF for the same size of operation assures us that in case our main operation is on the right path, the benefits outweigh the losses and, on the other hand, if our leading position in EUR / USD goes wrong, we get a profit on USD / CHF which, although not cover 100% losses, decreases significantly.
Related posts:
- Disparity Index
- Correlation yen
- A strategy on the exponential moving averages
- Trading strategy for those who work part time, part 2
- ADX – Average Directional Index
Tags: coefficient, financial terms, Forex, forex currencies