Introduction
Correlation Analysis is a statistical tool, used in market research to examine the relationship strength between multiple assets and to asses individual securities or broader market movements.
The key factor is the common evolution of the involved variables over a specific timeframe, producing correlations with positive or negative links.
The Pearson method
The most common method of measuring linear relationship correlations is the Pearson’s correlation coefficient, also knows as “Pearson’s R”. It is represented by a number between
-1 and 1, measuring the strength and direction of the relationship between the assets involved.
- (-1) signifies a strong negative correlation
- (0) represents no correlation.
- (+1) signals a strong positive correlation
*Graphic representation*
To minimise portfolio risk, diversification is most effective with uncorrelated or negatively correlated assets. However, correlation can only be retrospectively evaluated, as it isn’t static and the overall results could change overtime. Therefore, for optimal results, this tool should be combined with other technical strategies.
For example, Gold and the US Dollar are often associated with a negative correlation. Despite periods of positive correlation, their movement is generally opposite to each other.
Chart source: stockcharts.com
Conclusion
Correlation Coefficient assists investors in grasping the interdependence of certain portfolio assets, by offering key insights for diversification and risk management.
However, a crucial point to remember is that correlation isn’t the equivalent of causation, as external factors can influence the financial market securities.
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