The Cult of Beta
| Sep 15th, 2006 | Filed under: Performance, Analytics & Metrics | By: Alpha Male |
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By: Alpha Male
Before an unfortunate laboratory accident (involving mice trained to recognize Greek letters) left Alpha Male with strange blogging superpowers, he was a mild-mannered marketing executive with a $300 million long/short equity hedge fund. While at said hedge fund, Alpha Male learned a useful lesson about Beta:
All Betas are not created equal.
This statement may sound trite. Of course Betas are not created equal! You can have betas to an infinite number of factors from the S&P500 to the price of zinc to bond spreads, right? And by the same token, just because your portfolio has a beta-weight net exposure to the S&P500 of zero does not mean it has a beta-weighted net exposure of zero to zinc or spreads. Besides, Betas assume normality – which is not always a safe bet.
True and True and “True”. But I am referring here to betas to the same factor and I am assuming returns are normally distributed.
You can’t imagine the frustration experienced by the portfolio management team when a 1.0 beta stock falls out of bed on a day when the market was down only slightly. Why did this happen in the absence of news that might push it out of bed? On the same day, a stock with a beta of 0.9 might even have been up slightly. What gives?
The problem is that beta has been elevated by Bloomberg and Morningstar to cult status. Too often, investors blindly expect beta to predict short term security behavior. Perhaps in the 1970s when typical portfolio turnover was still under 500x a year, beta was a more useful measure. But it’s not a very useful metric in today’s short-term (hedge fund) investing world.
A quick trip back to finance class will illustrate why.
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[...] One challenge not always recognized is that beta, while somewhat intuitive, is not always well understood. This point was driven home to us in a post up over at the (new to us) All About Alpha blog. Their point is that beta is product of two different measures which can meaningfully change what beta really measures for any instrument. Read the whole post (and graphs) to get a fuller take on their interesting argument. [...]
[...] As we’ve discussed on this blog, beta is the product of two numbers: the correlation (r) and the volatility relative to the market’s volatility (i.e. volatility as a percentage of the market’s volatility). Let’s further assume that the beta of Stock “A” has an r-squared of 0.25 and the beta of Stock “B” also has an r-squared of 0.25. Basically, we’re not sure exactly how either stock will behave vs. the market as their correlations (r) are both only 0.5. [...]