Stock Picking Advice

I  came across some good advice below.  Be wary of the hype and use common sense.  Also be skeptical of the mathematical models, which appear to be based on the certainty of math, but really are based on subjective assumptions.

Shopping For Stocks? 5 Measures to Ignore

Investors are snatching up shares, but these numbers won’t help them pick winners or stay safe.


[smstockbroker] Getty Images

Stock investors are busy buying: The Dow Jones Industrial Average has jumped 480 points, or 4%, since last Friday. For those who are still shopping for shares, there is plenty of information to help them decide.

Few markets treat shoppers to as much comparison information as the U.S. stock market. Grocers list ingredients. Car dealers show performance metrics. Share-issuing corporations disclose not only what they’re made of and how prosperous they are, but also things like how they’re spending their money and what might go wrong in the future. The bosses must say when they’re buying or selling shares. There’s even an entire gossip industry that exists to speculate on things like future prosperity, messages hidden in the trading charts and whether shares are a good deal today.

It can be a bit overwhelming. Fortunately, investors don’t need nearly all available information to make buying decisions. Here’s an incomplete list of measures that can be safely ignored.

1. Beta

Beta is sometimes called a measure of risk. The ones cited for stocks are nothing of the sort, however. About a half century ago, economists created a formula that prices assets like stocks based on the returns they’re supposed to achieved. Returns are directly related to risk, the economists reckoned, so their formula depends greatly on a theoretical measure of risk called beta. The problem is that no one knows how to accurately measure risk in complex systems like financial markets. The betas listed on most stock quote websites are based on past trading volatility relative to a benchmark like the S&P 500 index. Over decades of testing, these volatility betas have failed to predict much of anything, let alone future volatility and returns.

Some comparisons using beta seem questionable. Is Amazon (AMZN: 209.49, 5.00, 2.45%) at 83 times earnings really much less risky than JC Penney (JCP: 35.03, 0.49, 1.42%) at 15 times earnings? Is thriving Google (GOOG: 521.03, 14.65, 2.89%) less reliable than struggling Yahoo (YHOO: 15.45, 0.41, 2.73%)? Stock buyers are better off doing what many professional investors do: Create your own “bottom-up” beta by simply scoring companies on common sense gauges of risk, like indebtedness and sensitivity to changes in the economic cycle. The result will be far less precise than volatility-based betas–and far more useful.

2. Share Price

Valuation matters a great deal to stock investors, but beginners sometimes get hung up on price alone. They shouldn’t. Share price doesn’t always relate to company price. Sprint Nextel (S: 5.43, 0.04, 0.74%) at $5 and change per share is more than four times as expensive a company as Panera Bread (PNRA: 130.28, 4.62, 3.68%), which recently traded at $127 a share, because the latter has far fewer shares outstanding. Also, what matters more than either the stock price or company price is how those things relate to underlying measures of value and prospects for growth. Green Mountain Coffee Roasters (GMCR: 90.35, 1.09, 1.22%) and Exxon Mobil (XOM: 82.01, 0.63, 0.77%)each recently traded between $80 and $90 a share. The oil producer sells for nine times earnings and is growing steadily. The coffee distributor sells for 60 times earnings and is growing frantically.

3. Average recommendation / price target

Wall Street hires an army of analysts to study companies, predict their profits and determine whether their shares are worth buying. The reports these analysts publish are plenty useful but the predictions aren’t. Studies have repeatedly shown that stocks with consensus “buy” recommendations don’t outdo those with consensus “sell” recommendations over long time periods. Even less reliable than the recommendations, however, are the price targets. Most are calculated using something called discounted cash flow analysis, which is a bit like sausage in that the less you know about how it’s made the more comfortable you’ll feel. Suffice it to say that analysts aren’t especially accurate when predicting this quarter’s earnings, and with DCF analysis, they must predict sales, margins, debt levels and more, not just for the current quarter but for the next decade or more. Then they have to risk-adjust the whole thing using — you guessed it — beta. Simple adjustments to the assumptions yield vast changes to the resulting price targets. Don’t let the specificity of the numbers fool you. Thick math layered over a foundation of guesswork is no cause for confidence.

One exception to the above: There’s evidence that changes in recommendations hold more predictive power than the average of recommendation at a particular time. So don’t be impressed that six out of 10 analysts say to buy a particular stock. Do take notice, however, if only four did so last week. But even then, use recommendation changes as a starting point for further research, not advice to be followed blindly.

4. Historical P/E

Such-and-such company sells for 13 times earnings, but it has traded at an average of 18 times earnings over the past five years, you might hear. It doesn’t mean much. Companies aren’t stagnant things. Their prospects can change quickly, as can those of the broad market. What matters more than how a company compares with its own past is how it compares with its peers and with the broad market, and how the market compares with its past. More impressive, then, would be that the same company sells for 13 times earnings while the average for its industry is 18 times earnings, and that the market sits at 15 times earnings, on par with its historic average.

5. PEG Ratio

The PEG ratio divides a stock’s price-to-earnings ratio by its projected earnings growth rate. The idea is to combine two important factors–valuation and growth potential–into one number that can be compared across industries. It’s a good idea, but I gave up on the PEG ratio years ago because it’s based on a key flaw, and it has nothing to do with the mathematical no-no of dividing a ratio by a percentage without first converting one to the other. (Your grammar school teacher says it’s OK in this case.) It’s the projections; most PEG ratios use a consensus of analysts’ long-term earnings growth projections. That’s a mess, because long-term growth is impossible to forecast with any accuracy, and numbers are often stale. Is AOL (AOL: 20.55, 0.69, 3.47%) really expected to grow its earnings by an average of 17.7% a year over the next five years? It must be in for a prosperous third, fourth and fifth year, because separate-year forecasts have its earnings plunging by more than half this year and recovering by only 11% next year. Either that, or long-term growth forecasts (along with the PEG ratios that rely on them) are bunk to begin with. Bet the latter.


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