So now we should have a collection of betas spanning from the start date to the end date of our dataset. Now what?
Now we have to see what all this data looks like visually. Trying to understand each individual cell is not a reasonable thing to attempt. It is much easier to create a graph so we know what we are looking at.
If you know how to make a histogram, then proceed on to the final section, “Interpreting Results”. Otherwise, follow along and I’ll show you how to make one.
A histogram – or frequency distribution – shows us how often a number comes up in our data. It creates a much easier and faster way of interpreting the data. They look like this:
In the above example, let’s imagine they are the lengths of different sharks in centimeters. Most of the sharks are about 100cm long. Fewer of them are 80cm or 120cm long, and even fewer still are 60cm and 140cm.
Our histogram is painting a picture of the AVERAGE shark length we can expect to see.
Now, let’s move on to the final step.
Select all the data points under “Slope”. In your spreadsheet program, insert a histogram graph. You should see something like this:
Each bar represents how many betas fall under the value shown on the horizontal axis. It’s a little messy and doesn’t tell us much, so let’s make some adjustments.
First, I like to have a lot of bars. Right now, our example only has 7, but I like to take the square root of the number of data points, and use that number to determine how many bars I should have. For example, the number of betas we have is 231. So, I’ll change the settings to have 15 or 16 bars. In Excel, this is done by right-clicking the horizontal axis and clicking Format Axis.
Now our histogram is officially a beta frequency distribution!
Now that we are done, let’s discuss just exactly what our frequency distribution graph is telling us, and how we can use that information in investing.