Turley Muller

High Beta Stocks: Plenty of Risk, Little Reward

The beta coefficient is not related to correlation. A line can be drawn through any set of data points no matter how unrelated the data points. The beta would just be the slope of the linear regression trend line, which is the "best fit" yet it could be a terrible fit relatively.

The R2- or coefficient of determination - explains the amount of variation of Y shared by X. Thus, if r2= .5 then it's explained as 50% of the the variation of StockABC is attributed to the variation of sp500.

The author mentions that some stocks (health care) have modest betas but are very volatile and have a low correlation to the market. This would suggest that the r2 would be 0 to .2 or so. Stocks like GE - which is very similar to the overall market might have .5-.6 or higher R2.

The Beta, or slope, just explains the relationship of Y to X - magnitude of change. Betas of .5 and 5 can be perfectly correlated with the market (r2=1), so beta doesn't explain the goodness of fit, just how x impacts y- If a stock moved 5 times as much than sp500, for every change, then the r2= 1 and the Beta would be 5.

My point is - (after longwinded diatribe) is that some Betas can be worthless. Absolutely worthless- This largely depends on how much the market's move is responsible for moves in the stock, the r2. Thus, that is an important factor to look at to evaluate Beta reasonableness.

There are many different estimations out there for any given stock.

AMZN-
Yahoo-3.3
Google-2.7
Value Line 1.2
MSN-2.95

Depends on the time frame used for the measurement.