How to Calculate Autocorrelation in Excel

Autocorrelation measures the degree of similarity between a time series and a lagged version of itself over successive time intervals.

It’s also sometimes referred to as “serial correlation” or “lagged correlation” since it measures the relationship between a variable’s current values and its historical values.

When the autocorrelation in a time series is high, it becomes easy to predict future values by simply referring to past values.

Autocorrelation in Excel

There is no built-in function to calculate autocorrelation in Excel, but we can use a single formula to calculate the autocorrelation for a time series for a given lag value.

For example, suppose we have the following time series that shows the value of a certain variable during 15 different time periods:

Time series example in Excel

We can use the following formula to calculate the autocorrelation at lag k =2.


Autocorrelation calculation in Excel

This results in a value of 0.656325. This is the autocorrelation at lag k = 2.

We can calculate the autocorrelation at lag k = 3 by changing the range of values in the formula:


Autocorrelation function for a time series in Excel

This results in a value of 0.49105. This is the autocorrelation at lag k = 3.

We can find the autocorrelation at each lag by using a similar formula. You’ll notice that the higher the lag, the lower the autocorrelation. This is typical of an autoregressive time series process.

Autocorrelation at different lags in Excel

You can find more Excel time series tutorials on this page.

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5 Replies to “How to Calculate Autocorrelation in Excel”

  1. I am confused by the formula you describe

    Using a lag of 2, sumproducts are calculated using 13 pairs, but divided by 15
    Using a lag of 3, sumproduct is calculated using 12 pairs, but divided by 15

    It will under-estimate the correlation as the lag is increased. Tested this using a sine wave. After 1 period of delay, the correlation was 0.7!

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