A friend at work recently asked me to look at some of the equities he holds in his portfolio. While I am a developer, I also have an MBA in Finance; I enjoy evaluating stocks and readily agreed.
One of my friend's holdings is Wal-Mart (WMT), and I was a bit surprised to see that finance.yahoo.com listed WMT's Beta, which is a measure of a stock's risk relative to the market, as -0.14. It is uncommon to find stocks with negative Betas. Generally this means that the stock moves in the opposite direction as the market. And the low Beta value, i.e. | Beta | < 1, indicates that the stock is less risky than the S&P500.
So I performed a few calculations, and measured the Beta for WMT using closing month prices for WMT and the S&P500 for the last five years, and reproduced the number listed on Yahoo! But I retried the calculation going all the way back to 1972, and got a Beta measurement of 1.23. And then again i measured beta for WMT only using the last 24 months of data and got a measurement of -0.31. (See graphs below for details).
WMT Calculation Beta - Last 60 Months (through March 2008)
WMT Calculation Beta - Data 1972 through March, 2008
WMT Calculation Beta - Last Two Years
So, given all of the variation in Beta measurements, what is a good way for estimating future Beta for a stock? This really is an important question, as Beta dominates the function to determine the Weighted Cost of Capital for a stock. (WACC = D/C ( Kd) + E/C ( Beta x Market Rate of Return). And if you are doing Beta arbitrage (buying baskets of low Beta stocks and short selling Beta stocks), this would be crucial. (Here's an interesting article on the subject... )
I suspect that modelers should make adjustments for changing legal environments, capital structurres, dynamics between companies and their customers, suppliers, and competitors... But which changes dominate Beta changes. Can the past Beta measurements be used at all to forecast future Beta?
Any ideas out there?
Interested in your thoughts,
Jonathan Starr