The Little Book That Makes You Rich by Louis Navellier & Forbes Steve

Author:Louis Navellier & Forbes, Steve
Language: eng
Format: epub
Publisher: Wiley
Published: 2011-01-05T00:00:00+00:00

Chapter Eleven

Don’t Be a Deviant

Deviance Is No More Appreciated in the Stock Market Than Anywhere Else in Life.

WHILE WE’VE COVERED the important topic of alpha and touched on risk versus reward, we need to delve into the concepts a bit deeper. I frequently hear a lot of talk by professional and individual investors about risk versus reward, but few of them offer a meaningful way to measure either. Some folks will point to various prices where they think that the risk for lower prices is higher or identify a price at which they think prices could rise, but this is poor guidance. As a numbers person, I knew that there had to be a better way to quantify and measure risk and reward, so I went looking for the answer and believe I have found it.

I do not want to sound like too much of a math geek, but a little explanation is necessary. Quantitative analysis is nothing more than applying mathematical theory to the movement of stock prices. We can chart stock movements and apply a series of statistical measurements to see how prices move in relationship to underlying market forces. Previously, I introduced you to the concepts of alpha and beta and how these measure each stock’s movement relative to the appropriate stock market benchmark.

Now I’ll introduce another character, a shady fellow who represents the excessive risk that needs to be avoided when owning growth stocks as measured by standard deviation or statistical variance. Standard deviation measures just how much a stock wiggles based on its trading range. When a stock’s price movement is too jerky and erratic—or volatile—it’s clearly a sign of bad things to come and needs to be avoided. That’s what standard deviation and my reward-to-risk measures help spot. In basic form, we divide a stock’s alpha (the return independent of the stock market that typically comes from buying pressure) by its standard deviation. We measure this over a 52-week period as we do with all our statistical measures. Any longer time frame than that is essentially too far back in the past and becomes less meaningful. For example, many quantitative analysts on Wall Street utilize five-year risk-and-reward measurements, but I think that’s just too long. What does price movement from five years ago have to do with today? That’s too far back in the past and would lead to measuring movement in different economic and market environments with little impact on today’s stock prices. My calculation gives us a number that I call the reward/risk ratio that determines my quantitative grade. Stocks with good reward/risk ratios tend to be lowerrisk stocks that are just plugging away, earning excess returns in a smooth consistent manner. These are the ones with the high quantitative grades that we want to own.

We recalculate these reward/risk measurements (e.g., alpha, beta, standard deviation, etc.) every weekend for every stock in my database. That’s almost 5,000 stocks. Any stock that trades 5,000 shares per day and has been trading for the

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