About: CAT, WMT, IBM, BAC, GE, (and the other 25)
Purpose: To suggest ways to put significantly different stocks on a directly comparable, relevant, and concise preference-ranking basis.
The initial effort to accomplish the purpose stated above was our article Comparing Incomparable Investments - ETFs which was either lightly read or heavily ignored.
Perhaps investors already have achieved such a system. More likely, they either think it cannot be done, or have not ever thought much about doing it, let alone how to. But anyone who has ever owned more than one stock at a time has encountered the need.
The above article focusing on ETFs points out that the system already exists, and the task at hand is just putting it to work. The way to do that is simply contracting-out the hard work to investment professionals, assembling the rankings, and evaluating them.
First, there has to be a single overriding purpose to the investment activity. We choose to identify that purpose as: "The most likely means to build significant personal wealth through a time period."
Other objectives, like updating one's knowledge of the advances in technology, medicine, international politics, entertainment and the arts may be desirable, but are secondary. Knowing the inside story of why a corporate executive left one job and is now at another, may be titillating, but is not essential. Nor is what this year's fashion color is.
The wealth-building objective helps to identify the existing ranking system. A few thousand professional investment folks are at this task every market-transaction day.
They work at market-making firms, helping big fund clients make adjustments, in volume, to billion-dollar portfolios. Their cohorts make it possible for comparable market pros at other such firms to fill similar orders by selling them price insurance on that part of the trade that the market otherwise could not absorb. This provides "market liquidity."
The hedging activity that underlies the liquid markets in widely-held and actively-traded stocks (and ETFs) contains well-informed judgments about the probable future price moves of each issue. The seven and eight-figure annual salary and bonuses of these market pros are justified by those judgments. We know how to reveal the extents of their expectations, both as to higher and lower likely prices.
So there is a moment-by-moment process already in existence, based on the prop desk's decision of at what price to sell (and by a block desk's decision of whether to buy) risk protection. Both buyer and seller are highly motivated and well-informed.
But are their decisions of the moment useful to investors, intent on wealth-building across time?
Here is a valid test: Take the top end of the future range of prices for the stock, implied by the purchase of risk insurance (by a market-liquidity short-seller of said stock) as a sell target for a prospective investor. Set a new purchase of the stock at the market price when the forecast was made, with a time limit of patience to hold. See if the target is reached before patience expires, or else what the result would be at that end point in time.
Repeat the test for the stock every market day for several years.
Then look at the current forecast to see where today's price lies in the range of possible future prices expected (the Range Index).
Find all prior forecasts with Range Indexes at least as attractive as today's, and compound their return results (1 + the price change) x each result to get the mean result+1.
The mean results may be directly compared with other stocks' mean result+1 where the average holding periods from the tests are about the same. Where they are not, the better measure is to annualize the rates of return in each case.
Let's see how that works out today for the DJIA stocks. Their average annual rate of gain as represented by the Dow-30 industrials index since the start of 2000 has been 1.3% per year.
We put all 30 DJ stocks to this test during those years. Their overall average annual rate of return for those periods where each stock would be invested, based on their present-day Range Indexes, is 7.8%, a 650 basis point advantage over an index buy and hold.
This is merely an illustration, not an argument that now is an especially favorable time to be buying the DJIA. Nor for buying all of the index's stocks today. It does say that market-makers do appear to have useful timing insights at varied points in time on some of the most intensely-studied stocks, perhaps even at randomly-chosen points in time. That should not be a surprise, since their jobs depend on it.
Of more specific interest right now might be the DJIA stocks that offer the most and least attractive prospects, currently. So here is a table of five of the best and three of the worst, using CAT as an explanation of the column headers and data details.
Caterpillar (CAT) has had 488 prior forecasts at least as attractive as today's, averaging gains of 4.6% in typical holding periods of seven weeks, at typical annual rates of +40%. Odds of profitable experience: 68 out of 100. Average blind 1-year buy&hold gain: +15%, win odds 72 out of 100.
All days are market days, 252 per year, with annual rates appropriately calculated from average daily changes.
This is only an illustration of the differences in prospects for well-followed stocks at a point in time, not a screaming buy signal for, say CAT. The point is that every day professional forecasts are being made, and at varying times the current forecast has a strong record of being followed in the past by very attractive investment returns in a high proportion of cases.
Two good contrasting examples of that at the moment are Apple (AAPL), whose current Range Index of 13 has 43 priors that produced average gains of 5.4% in 28 days for an annual rate of +58%, and Cirrus Logic (CRUS), whose 158 prior current Range Index indications captured +13% gains in 27-day holds for an annual rate of +205%.