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Intermediate
Beta is a measure of market-related risk. It is the slope of the line of best fit from a single-variable linear regression of the asset returns (y-axis) versus the Market (x-axis). Beta is a key component of the Capital Asset Pricing Model (CAPM) and is used in asset valuation and for calculating the cost of capital in corporate finance.
Synonym: beta coefficient
Bev: Ann, when we report our
beta we really should
include r-squared to see how valid beta is, right?
Ann: I think so. But I guarantee Kay and Jim
in Sales will say it's overkill.
This video can be accessed in a new window or App , at the YouTube Channel or from below.
Beta definition for investment modeling (4:11)
The script includes two sections where we visualize and demonstrate the calculation of beta.
We're sitting right here in Excel, and this is a snippet from our boot camp course.
Here we plotted 60 monthly returns on the stock Merck on the y-axis. And 60 monthly returns on the Market on the x-axis, for the same time period.
So for this one month the Market was up 10% and Merck was up 14%.
This line of best fit minimizes the differences between the line and each of the points. That's what linear regression does.
The slope of this line, in the formula here, is 1.2274. That is beta. And the formula for the line, given in y = mx + b format, reads like this: to estimate the monthly return for Merck, multiply the Market return by 1.2274 and then subtract 0.0074.
Again, beta is a measure of market related risk. Notice it isn't an absolute measure of risk like volatility, also known as standard deviation. Beta is used to see how Merck's returns relate to movements in the Market (ie, relative to the Market).
And for cost of capital calculations, this is highly simplified, but if you expect equities to go up by 6%, then the cost of capital for Merck was 6% * 1.2274 or 7.36%. Next, let's demonstrate.
There are four ways to generate regression statistics in Excel. First, you can use the chart output, but that isn't the easiest.
A lot of people use the Data Analysis method, with output like this, and beta is down here in the coefficient column.
Third is the function method, where you use the function called
=SLOPE()
. Input the stream of returns
for the y-variable first, then comma, then the x-variable and hit
Enter.
Fourth is the =LINEST()
method which
gives added functionality but is too advanced to cover here.
Click box for answer.
7.86%
Still unclear on beta? Leave a question in the comments section on YouTube or check out the Quant 101, specifically How to find the expected return on a stock using the CAPM Model.
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