Cultivating New Data With The Stock Index Calculator


I don’t know about you, but in my neck of the woods the weather has been absolutely beautiful lately and unseasonably warm for a February day.  The sunny days have made me start to think ahead to the garden in my back yard and how I might want to improve it this year.  Some of that will require a bit of cleanup, and some is about finding new plants to complement what did well last year.  I don’t naturally have a green thumb, but I’ve found that persistence is a virtue.  Every year the garden is a little better than before.

In that same spirit, as part of the necessary site data cultivation effort I just finished updating the Stock Index Calculator with new data.  

For anyone unfamiliar with the project, I’d recommend starting with this post.  Long story short — good historical stock index data is surprisingly difficult to find without paying an arm and a leg, so I decided to do the heavy lifting myself.  The stock index calculator models all nine US size and value indices from large to small and value to growth all the way back to 1927 based on source data from the wonderful Fama French data library.  It serves as the foundation not only for my own calculations but is also used as a source in the Simba Spreadsheet.

Everything runs the same as before, but there are two important changes.  First, I’ve added 2016 data.  And second, I’ve updated all of the annual returns based on new information in the Fama French library.  We’re mostly talking a few basis points here and there, but it’s true that many numbers have changed.

I’ll be updating all of the calculators with the new data soon, as they’re important not only for the returns numbers but also for the verified/estimated calculations.  I do not expect most people to notice any differences, but I aim to be as accurate as possible.  In the meantime, anyone who happens to use that data in their own calculations might want to visit the page and download the new spreadsheet.

As always, if you spot a mistake please let me know.  Good data is a passion of mine, and I’m always open to feedback and ideas.