A recent study attempted to classify hundreds of factors according to their degree of non-correlation. See my review of it here: https://blog.portfolio123.com/thoughts-on-is-there-a-replication-crisis-in-finance/
If you want to study the correlation of factors, here’s what I suggest. Create a one-factor ranking system. Run the performance test using no more than 10 buckets (5 might be easier), but click on “performance” rather than “annualized returns,” and don’t use the default universe, but a universe with reasonable liquidity. Download the result.
Let’s say you’re using ten buckets. You’ll get ten columns of numbers. Create a second ten columns with the formula =C14/C13-1 and so on so that each column collects the percentage returns from the corresponding column. Let’s say those are columns N through W.
Now create a row somewhere with the numbers 0.1, 0.2, 0.3 . . . up to 1.0. Let’s say you create it in row 12, cells N12 through W12.
Lastly, create yet another column with the following formula: =SLOPE(N14:W14,N$12:W$12) and copy that down the row. That will be the slope of the ten bucket return during every month of your backtest.
Perform the performance test on another factor, and then another, and another, and each time paste the results into the first file you created. Save the slope columns in a separate spreadsheet and label them all. Then create a correlation table. You can do this using the “Data analysis” tool in the Data tab of your Excel file.
I think you’ll find this a very useful tool to discovering factors that are correlated or uncorrelated in terms of their performance. Once you’ve set up the initial Excel file, it’s not terribly difficult. I’ve attached an Excel file I created using one factor with the slope column clearly labeled, just in case my directions were unclear. Columns A through L consist simply of the output of my performance test.
slope through time.xlsx (58 KB)