A negative correlation between two variables means that one variable increases whenever the other decreases. This relationship may or may not represent causation between the two variables, but it does describe a pattern.
Perfect negative correlation means that the relationship is demonstrated consistently over time. A decrease in one variable predictably meets with a comparable increase in the other.
Statisticians assign a negative value to negative correlations and a positive value when a positive correlation exists. Correlation is measured on a scale of -1 to +1.
Understanding Negative Correlation
When two variables are correlated, the changes in their values may have the same cause or a related cause. In a negative correlation, the increase of one variable may represent the direct cause of a decrease of another factor.
- A negative correlation is shown between two factors that move consistently in opposite directions.
- Investors might use negative correlation to reduce the level of risk in their portfolios.
- That is, when one category of stocks tanks, another with a negative correlation will stay steady or rise.
If, for example, the indoor population numbers of mice and cats are negatively correlated, then an increase in the cat population may directly cause a decrease in the number of mice.
The correlation may be unrelated, however. Another factor, such as the introduction of new mouse traps, could be decreasing the number of indoor mice. If the cats are very lazy, they may well have contributed nothing to the reduction in the mouse population.
How Investors Use Correlations
Many investors study correlations between stocks, between industries, and between asset types in order to reduce risk in their portfolios.
For example, an investor in oil might hedge a portfolio with stocks in airlines. The two industries have a negative correlation. When oil prices slide, airline stocks rise.
In business, correlations should be investigated to determine their cause. Business planners may look at existing relationships between variables, such as marketing expenditures and sales, as part of market analysis.
A correlation may or may not be meaningful. Many complex factors could be in play.
However, correlations should not be too quickly interpreted as evidence of one variable causing a change in another variable. Business environments often present highly complex causes and correlations that may or may not be meaningful.
For example, an increase in consumer spending on a product may occur at the same time as positive media coverage of that product. It is tempting to assume that positive media coverage was the cause of the increased spending. But many factors can boost sales, from improved packaging to introduction in a new market to seasonal swings in demand.
Weak and Strong Correlations
The strength of a negative correlation can vary. That is, one variable might increase by 5% while another variable decreases by only 1.5%. They have a weak negative correlation.
Two factors are said to have a perfect negative correlation if each of those factors always moves by the same amount. If, when one variable increases by 2%, the other variable always decreases by 1.6%, they have a perfect negative correlation.
In a perfect positive correlation, the same consistency in movement between factors is shown.