A:

In the financial world, R-squared is a statistical measure that represents the percentage of a fund or a security's movements that can be explained by movements in a benchmark index. Where correlation explains the strength of the relationship between an independent and dependent variable, R-squared explains to what extent the variance of one variable explains the variance of the second variable.Â  The formula for R-squared is simply correlation squared. (Want to learn more about excel? Visit Investopedia Academy for our excel courses).Â

## Common Mistakes with R-Squared

The single most common mistake is assuming an R-squared approaching +/- 1 is statistically significant. A reading approaching +/- 1 definitely increases the chances of actual statistical significance, but without further testing it's impossible to know based on the result alone. The statistical testing is not at all straightforward; it can get complicated for a number of reasons. To touch on this briefly, a critical assumption of correlation (and thus R-squared) is that the variables are independent and that the relationship between them is linear. Â In theory, you would test these claims to determine if a correlation calculation is appropriate. Â

The second most common mistake is forgetting to normalized the data into a common unit. Â If you are calculating a correlation (or R-squared) on two betas, then the units are already normalized: The unit is beta. Â However, if you want to correlate stocks, it's critical you normalize them into percent return, and not share price changes. Â This happens all too frequently, even among investment professionals. Â

For stock price correlation (or R-squared), you are essentially asking two questions: What is the return over a certain number of periods, and how does that variance relate to another securities variance over the same period? Â Two securities might have a high correlation (or R-squared) if the return is daily percent changes over the past 52 weeks, but a low correlation if the return is monthly changes over the past 52 weeks. Â Which one is "better"? There really is no perfect answer, and it depends on the purpose of the test. Â

## How to Calculate R-Squared in Excel

There are several methods to calculating R-squared in Excel.

The simplest way is to get two data sets and use the built-in R-squared formula. Â The other alternative is to find correlation, then square it. Both are shown below:

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