Brad, its good to talk to someone with firm backround in market theory, and I appreciate the opportunity to exchange views with you. You raise several issues which are of interest to me- too many for me to respond to in one post, so I'll start with betas.
Since beta is the slope of the regression line of a stock's holding period rate of return against the the market's HPRR, you would expect that a high beta portfolio would underperform the broader market when the market is down, and I believe that is clearly the case with larger cap stocks. Although I haven't studied it, I believe it may not hold true for small caps. The usual interpretation of beta is "volatility", but I've been of the opinion for some time that that is an incorrect interpretation. It is my belief that beta is more like leverage, magnifying the swings of the market. It would seem to me that the standard deviation of beta is a better measurement of "volatility". If you look at the regression line drawn through the points, it would seem to me that the closer the points are to the regression line, the smaller the volatility. In other words, if you take the square root of the sum of the squared residuals divided by the number of residuals, isn't this a better measure of "volatility"?
From a practical point of view, I've been using Value Line for over 20 years, and I've found that it consistently beats the market. VL commissioned some academic people to look into their claims, and the studies confirmed VL's assertion that their #1 timeliness picks significantly out-performed the market. The people who performed the studies frankly admitted their surprise at the results, and forced them to ammend their views of the "efficient market hypothesis". When you think about it, that hypothesis (in the strong form) has theoretical problems since it tacitly assumes that all public information about a company is instantaneously reflected in the price of a security. But if you study the relationship between the release of news and stock prices you can clearly see a period of time that it takes for a stock to reach a new "trading range". This is particularly true of the smaller, less widely followed issues. While hardly a "scientific" demonstration of what I'm talking about look at the behavior of SEG following earnings warnings from the company. This is especially noteworthy in the era of the internet, where news is more rapidly and widely disseminated than ever before.
I believe that the reason the "dogs of the Dow" works is the result of this phenomenon. That is, the market tends to over-react to bad news. How else does one explain the "Foolish Four" results?
My personal response to these factors is to stay fully invested in a portfolio of growth companies, and to sell only when the underlying long-term growth story deteriorates. Using this approach I have consistently out-performed the market, although not for every quarter. But over the long haul my returns have averaged about 50% better than the market.
I look forward to hearing from you.
Regards,
Paul |
