We now need to calculate the k-th lag variance.įor k=1, covariance will be calculated as follows:įor k=2, covariance will be calculated as follows:Īutocorrelation can now be calculated as follows:Īutocorrelation (k=1) = 0.000469/0.0001 = 4.69Īutocorrelation (k=2) = 0.000469/-0.00027 = -1.737Īutocorrelation is commonly referred to as ACF in formulas. The variance of the series can be calculated using the VAR formula as follows: Let’s say we have the following stock returns data with us. Let’s take a numerical example to learn how we can calculate the autocorrelation for stock returns data in excel. The only difference is that while calculating autocorrelation, you use the same time series twice, one original, and the other as the lagged one. If you observe that the stock is moving up for the past few days, you can expect the stock movement to match the lagging time series.Ĭalculation of autocorrelation is similar to calculation of correlation between two time series. For example, let’s say you identify a stock that has exhibited high autocorrelation historically. We can calculate autocorrelation in stock returns which can be helpful in equity analysis. Autocorrelation is calculated as a function of mean and variance.Īutocorrelation has application in stock returns. The observations are said to be independent if autocorrelation is zero. Autocorrelation, also known as serial correlation or lagged correlation, explains the relationship between observations between the same variable over different periods of time.
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