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Correlation definition and tutorial

People use the term correlation loosely without fully grasping its context and limitations. For portfolio management, properly demonstrating this understanding is a path to success.
  1. Define - Define the Correlation Coefficient.
  2. Context - Use Correlation in a sentence.
  3. Video - See the video.
  4. Script - Read the transcript.
  5. Quiz - Test your knowledge.
by Paul Alan Davis, CFA, July 29, 2016
Updated: December 22, 2018
In investments, negative correlation can be as meaningful as positive correlation. Keep reading to learn why.

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Correlation for Investment Modeling


Correlation is a measure of the co-movements between data points. It is used in risk measurement of securities or factors. There is one correlation per pair of assets, not one per asset. It is more interpretable than the related covariance measure because the scale ranges from -1 to +1. To calculate, take the covariance between each pair of assets and divide by the product of the standard deviations.

Synonym: correlation coefficient

In a Sentence

Ali:  Doc, why doesn't the Excel function =CORREL care about variable order?
Doc:  Remember, correlation  is not causation, so order doesn't matter.


This video can be accessed in a new window or App , at the YouTube Channel or from below.

Correlation definition for investment modeling (4:41)

Video Script

The script includes two sections where we visualize and demonstrate the calculation of correlation.


We're sitting in Excel, and this is a snippet from our boot camp course.

This is one depiction of correlation, from a scatterplot of returns for one stock, Merck, versus a basket of stocks, the Market, for 60 periods. Think about each dot here as return for the Market on the x-axis and Merck on the y-axis, for each month.

So if stocks exhibit co-movements, as they appear to here, then a pattern will look linear. A random shotgun pattern would have low correlation.

This is an example of positive correlation because a rise in the Market, corresponded with positive movements for Merck. A line sloping to the left demonstrates negative correlation. The calculation helps us understand correlation, so let's head there now.


Let's walk through a calculation for two stocks, Microsoft and eBay.

We have six monthly returns for each stock from April to September 2003. Column F is the return on Microsoft. eBay is in column G. Next we compute the average of each, here 2.38% and 3.98%. Then move those over to columns H and I.

In column J, take the return minus the average which gives us 3.24%. That's 5.62% minus 2.38%. For eBay it is 8.91% minus 3.98% or 4.93%. Carry that formula down, and let's call these demeaned returns.

Next, in column L, multiply these together. As you notice, when the stocks moved together, like in April, the product is positive. And when they moved in opposite directions, the product is negative.

Next, using the =SUM() function, add up the products to get -0.0037 for the pair of stocks. Next, divide by 6 observations for a covariance of -0.0006. This isn't interpretable as the units are in returns-squared, so we translate it to correlation by dividing by the product of the two standard deviations.

So to interpret, these two stocks had negative correlation, meaning as one moved up, the other moved down. These would be examples of diversifying stocks. And the reading of 0.45 means that the points are fairly tight around the line of best fit.


Click box for answer.

In the social sciences, like economics, correlations above 0.70, and below -0.70, are considered high. | True or False?


Questions or Comments?

Still unclear on correlation? Leave a question in the comments section on YouTube or check out the Quant 101 Series, specifically Four Essential Stock Risk Measures and How to Interpret Correlation and R-squared

Related Terms

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