If you ever took a statistics class, the title of this section may have filled you with a little trepidation and dread. Have no fear; I will not ask you to compute Pearson’s *r* by hand. The basic idea of a correlation, though, is critical to the investor. The more alike two stocks are, the more they will move up and down in price together. More accurately, the more the economic drivers of profits for the underlying companies are similar, the higher the correlation will be. If Ford had a terrible year last year because of a spike in steel prices and the stock declines when earnings are reported, then you can expect a similar decline in the stock of GM even though GM hasn’t reported earnings yet. If Budweiser sales are down, then the stock of Coors is likely to go down in **sympathy**, which is market jargon for a correlated fall in price.

The more unlike two stocks are, the less we expect them to be correlated. Strangely enough, all stocks are correlated to some degree, especially when there is a rapid market-wide decline. When we look at our overall exposure to risk (what we will later call *portfolio risk*), we must consider two factors. The first is how our portfolio will do in a down market. Day to day declines in individual stock prices are taken care of by diversifying our holding of stocks. If we own a broad basket of 500 large US companies, the fall on one price will be made up for by a rise in another. We don’t even notice the underlying price action when we look at the value of our stocks.

Note that not only stocks can be correlated. Different asset classes (e.g., bonds, real estate, and gold) can be correlated as well. In the final chapter, we will examine how we can build safer portfolios by considering correlations between assets and asset classes and systematically reducing them.

### Correlation Coefficients

The degree to which two securities are correlated can be translated into a statistic called a correlation coefficient, which has a value that must fall between -1.00 and 1.00. The sign tells us nothing about magnitude.

A positive correlation means that when one stock goes up, the other one goes up with it. The bigger the number, the better you can predict the movement of stock Y by knowing the move in stock X. If the correlation is 1.0 (a perfect correlation), then we know that whenever X moves up $1, then Y will move up $1.

A negative correlation means that movements in stock Y can be predicted by knowing the movement in stock X, but Y goes down when X goes up and vice versa. Traders often use the term inverse to describe this type of relationship. If the correlation is -1.0, then we know that when X goes up $1, then Y will go down $1.

Uncorrelated means that the price of two instruments goes up and down independent of each other.

It is critical to note that correlations between investments are dynamic and not static, meaning that two uncorrelated investments can become correlated in the future and vice versa.