What it is:
Negative correlation describes a relationship in which changes in one variable are associated with opposite changes in another variable.
How it works (Example):
For example, many economists have discovered that people tend to buy more candy and liquor during recessions. Recessions are characterized by a variety of factors, particularly a decline in spending on discretionary items such as luxury goods, restaurants and travel. Thus, one could expect a negative correlation between, say, hotel stocks and candy stocks. In other words, when hotel stocks are down across the board, candy stocks will probably rise across the board.
Statistically speaking, the correlation between any two variables ranges from -1.0 (perfectly negatively correlated) to 1.0 (perfectly correlated). Analysts can also determine whether two things are negatively correlated by running a regression analysis on the two items and then calculating their R2. R2 is a statistical measure of how well one thing (often a financial model) predicts the value of another thing (typically a security or a portfolio). The higher the R2, the more positively correlated two things are. Beta is also a common tool for measuring how correlated a particular security or group of securities is to a broader market index or group of stocks. A beta of 1.0 indicates perfect correlation (meaning that when one goes up, the other does too).
Why it Matters:
Negative correlation is the essence of hedging and diversification. After all, if an investor can find an that consistently goes in the opposite direction of another investment, then holding both can virtually portfolio stability. That’s because when one investment loses value, the other investment gains value, thereby creating a situation in which the investor “can’t lose” (it also creates a situation in which he or she “can’t win,” too). Accordingly, negative correlation is a way to reduce risk. Investors who wish to increase their risk exposures (and, correspondingly, their potential returns) tend to avoid integrating too much negative correlation into their portfolios.
It is very important to remember, however, that correlation does not positive correlation between two variables does not exist under every circumstance.