Negative Correlation Definition

What is negative correlation?

Negative correlation is a relationship between two variables in which one variable increases while the other decreases, and vice versa.

In statistics, a perfect negative correlation is represented by the value -1.0, while a 0 indicates no correlation and +1.0 indicates perfect positive correlation. A perfect negative correlation means that the relationship that exists between two variables is exactly opposite all the time.

Key points to remember

  • Negative or inverse correlation describes when two variables tend to move in an opposite size and direction to each other, such that when one increases, the other variable decreases, and vice versa .
  • The negative correlation is taken advantage of when constructing diversified portfolios, so that investors can benefit from the price increases of certain assets when others fall.
  • The correlation between two variables can vary considerably over time. Stocks and bonds generally have a negative correlation, but over the 10 years to 2018, their measured correlation has ranged from -0.8 to +0.2.

Understanding Negative Correlation

Negative correlation or inverse correlation indicates that two individual variables have a statistical relationship such that their prices generally move in opposite directions with respect to each other. If, for example, the variables X and Y have a negative correlation (or are negatively correlated), as X increases in value, Y will decrease; similarly, if X decreases in value, Y will increase.

The degree of variation of one variable relative to another is measured by the Correlation coefficient, which quantifies the strength of the correlation between two variables. For example, if the variables X and Y have a correlation coefficient of -0.1, they have a weak negative correlation, but if they have a correlation coefficient of -0.9, they would be considered to have a strong negative correlation .

The higher the negative correlation between two variables, the closer the correlation coefficient will be to the value -1. Similarly, two variables with a perfect positive correlation would have a correlation coefficient of +1, while a correlation coefficient of zero implies that the two variables are uncorrelated and move independently of each other.

The correlation coefficient, usually denoted by “r” or “R”, can be determined by regression analysis. The square of the correlation coefficient (usually denoted “R2“, Where R squared) represents the degree or extent to which the variance of one variable is related to the variance of the second variable, and is usually expressed in terms of a percentage.

For example, if a wallet and its reference have a correlation of 0.9, the R-squared value would be 0.81. The interpretation of this figure is that 81% of the change in the portfolio (the dependent variable in this case) is related to – or can be explained by – the change in the benchmark (the independent variable).

The degree of correlation between two variables is not static, but can oscillate over a wide range – or from positive to negative, and vice versa – over time.


Charts showing positive, negative, and uncorrelated.
Illustration by Hugo Lin. © 2018 ThoughtCo.

The importance of negative correlation

The concept of negative correlation is essential in wallet construction. A negative correlation between sectors or geographies allows the creation of diversified portfolios capable of better resisting market volatility and smoothing long-term portfolio returns.

The construction of large and complex portfolios where correlations are carefully balanced to provide more predictable volatility is generally referred to as the discipline of strategic asset allocation.

Consider the long-term negative correlation between stocks and obligations. Stocks generally outperform bonds during periods of strong economic performance, but as the economy slows and central bank cuts interest rates to stimulate the economy, bonds can outperform stocks.

For example, suppose you have $100,000 balance portfolio invested 60% in equities and 40% in bonds. In a year of strong economic performance, the equity component of your portfolio may generate a return of 12%, while the bond component may generate a return of -2%, because interest rate are on an upward trend. Thus, the overall return of your portfolio would be 6.4% ((12% x 0.6) + (-2% x 0.4).

The following year, as the economy slows dramatically and interest rates fall, your stock portfolio may generate -5% while your bond portfolio may generate an 8% return, giving you a return overall portfolio of 0.2%.

What if, instead of a balanced portfolio, your portfolio was made up of 100% equities? By using the same come back assumptions, your all-equity portfolio would return 12% in year one and -5% in year two, which is more volatile than the balanced portfolio returns of 6.4% and 0.2%.

Shares and bonds generally have a negative correlation, but over the 10 years to 2018, their correlation has ranged from around -0.8 to +0.2, according to BlackRock.

Examples of negative correlation

Examples of negative correlation are common in the investment world. A well-known example is the negative correlation between crude oil airline stock prices and quotes. Kerosene, which is derived from crude oil, represents a significant cost for airlines and has a significant impact on their profitability and earnings.

If the price of crude oil skyrockets, it could have a negative impact on airline profits and therefore on their stock prices. But if the price of crude oil tends to fall, it should boost airline profits and therefore their stock prices.

Here’s how the existence of this phenomenon can help in building a diversified portfolio. As the energy sector has a substantial weight in most stocks clues, many investors are heavily exposed to crude oil prices, which are generally quite volatile. As the energy sector, for obvious reasons, has a positive correlation with crude oil prices, investing a portion of one’s portfolio in airline stocks would provide a hedge in the face of falling oil prices.

Special Considerations

It should be noted that this investment thesis may not work all the time, as the typical negative correlation between oil prices and airline stocks can sometimes turn positive. For example, during an economic boom, both oil prices and airline stocks may rise; conversely, during a recessionoil prices and airline stocks could fall in tandem.

When the negative correlation between two variables breaks down, it can wreak havoc on investment portfolios. For example, US stock markets posted their worst performance in a decade in the fourth quarter of 2018, fueled in part by fears that the Federal Reserve (Fed) would continue to raise interest rates.

Fears of a rate hike also weighed on bonds, causing their normally negative correlation with equities to fall to the lowest levels in decades. At such times, investors often discover to their chagrin that there is no place to hide.

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