Some even do better than the best Dow-Jones Stocks
Wealth-builder stocks are the ones which most reliably rise in price in big amounts in short periods of time. We look for them by the way they scare market-making [MM] professionals who have to short-sell them temporarily.
The MMs have to do that when one of their big fund-manager clients wants to buy a lot of one stock all at one time. It happens often because the big buyers know that if they try to only buy a few thousand shares at a time, and keep on doing that repeatedly, other stock sharks will smell rising prices in the market water and rush in ahead of the biggie to buy when the price is low. So the fund-manager client wants to buy all of what they need at once.
But there are rarely that many sellers supplying the immediate demand. So the MMs know where to borrow shares to sell to the clients. Then, later on the MMs can make covering buys to return the borrowed shares they sold to the client.
Only, if the borrowed stock shares rise in price in the meantime, the MMs will lose money. So they buy price-change “insurance” against that happening. If the MMs are really scared, they buy a lot of insurance to cover their short position. That’s what we want to see, and it’s hard for MMs to hide when it happens.
So we watch thousands of actively-traded stocks every day to see those warning signs. Today the stocks of companies providing computer programs and systems -- which do all sorts of neat work-saving activities -- look like what the investing organizations managing Billion-dollar portfolios are interested in buying. All at once. Some stocks much more than others.
Figure 1 is a map of how scared the MM buyers of the insurance are about the stocks going up. And how scared the sellers of the insurance are that the stocks might go down – where the insurance buyers might benefit instead, at their expense. Every stock in Figure 1 has a balance point range where the expectations of a stock’s future prices lie between the notions of the insurance negotiators' high and low price expectations.
(note: all materials from blockdesk.com have been approved for use in this article)
The upside price rises feared by MMs are measured by the green horizontal scale, while the downside actual market price drawdowns previously experienced by investors following upside forecasts like those of this day are measured by the red vertical scale. Intersections of those two coordinates are indicated by the ticker symbols in the blue field at right of the stocks involved at the numbered locations.
Both scales are of percent change from zero to 25%. Any stock or ETF whose present risk exposure exceeds its reward prospect will be above the dotted diagonal line.
Best reward-to-risk tradeoffs are to be found on this map at the frontier of alternatives, down and to the right. Outstanding illustrations in the green area are Adobe Inc, (ADBE) at location  and Blackbaud, Inc. (BLKB) at .
This map is a good starting point, but it can only cover some of the investment characteristics that often should influence an investor’s choice of where to put his/her capital to work. The table in Figure 2 covers the above considerations and several others.
More Useful Details
There is a whole mess of numbers here, and if this is the first time you have seen it, just getting hold of what is where is exhausting. Hopefully, after a few more looks (and several more will be offered in the normal flow of articles), you may be ready to join those now who will be getting a deeper perspective into what data levels separate one prospective investment candidate from another.
All perspectives begin, of course, with the price range forecasts [B] to [C] implied from the actions by negotiators for purchase of price-change protections in the derivative securities markets. Those ranges of what are both possible and likely are defined by the interplay of a set of hedging contract relationships in futures, options, swaps and other more exotic financial positions. How that is done is less important than what the ranges imply.
We learn the implications by seeing how equities markets have responded in periods following the forecasts. Of course, those responses from time to time have not been identical, due to the surrounding circumstances. But they have provided senses of central tendencies, averages and extreme limits, and measures of diversity. They offer guidance rather than any precise set of scientific rules.
But humans are creatures of habit and there can be great value in reasonably-bounded imperfect expectations followed consistently and with gradual adaptions. So when we see a set of experiences like those for Adobe Inc. (ADBE) in the first row of Figure 2 which says that the worst-case price drawdowns following 36 prior forecasts [L] like that of this day, we know it does not say there cannot be any losses greater than -1.9%.
Since that -1.9% [F] is an average of 36 periods of different starting dates over the course of 1,261 market days (5 years) [M] there are undoubtedly both greater and lesser price drawdowns than -1.9%. And they occurred at various points in the average holding periods of 36 days. In fact, none of the worst ones (or for that matter, of any price drawdowns below ADBE position entry costs) were still in negative territory at the end of the holding period, since the Win Odds are shown in [H] to be 100 out of 100, proportionally. Actually 36 out of 36.
And while 36 instances may be “statistically” impressive under the right circumstances of the 1261 market days, it is only one sample which ought not to be extended beyond the defining character of its selection definition: In this case an upside-to-downside forecast with about 3 times as large an upside as a downside price-change expectation – what is meant by the Range Index of [G] at 23.
Given that in 5 years there are 60 months, the 36 sample is little more than a once-every-other-month occurrence. But it is far better than the problematic samples of only 6 (of 1261) for Blackbaud, Inc. (BLKB) or only one for RHT.
The summary blue rows at the bottom of Figure 2 offer some further perspective in this Sample Size [L] column matter. Of the 2,660 equities for which we have credible and acceptable forecasts, there were 96 with the average proportions (upside to downside) of the whole population (a RI of 24). So while there should be some comfort in the 36 sample size for ADBE, it is not an unassailable convincer.
Similar relationships between individual security experiences and the larger population averages may be more reinforcing. Going back to the [F] worst price drawdown column, ADBE’s -1.9% is much better than the population’s -9.1%. But then, the drawdown exposure of market index SPDR S&P500 ETF (SPY) is only -1.4%. Quite small at present, despite all the terrible imaginings foreseen by many market observers. Still, beyond the next 3 months, such bets don't count, and there are useful actions to be taken in the interim.
Perhaps more is accomplished here by going on to the basic purpose of the article, the propensity of specific stocks to achieve price gains in a fairly brief period of capital commitment.
Towards the goal
With so many moving parts involved it is useful to reduce their number by combining related ones. Given adequate sample sizes, the odds of success [H] and failure [100-H] can be combined into their benefits [ I ] and costs [F]. That done in [O] and [P], they are combined in [Q]. That cluster of 4 variables is reduced to one.
Another related dimension of time efficiency (speed of change) can be combined by conditioning [Q] with [ J ] to measure net likely price changes in terms of basis points per day [R]. Then a table like Figure 2 can be ranked by bp/day, as it is.
An all-forecasts-population average (of more than 2,600 securities), the widely-accepted equity market average S&P500 Index ETF (SPY), and an average of the population's best 10 securities' prospects (and histories), provide a sense of the relative attractiveness of each of the securities' rows in Figure 2, column by column.
But choosing where to commit capital between attractive alternatives is still a thought-provoking exercise, since quality of conviction is not always satisfied simply by a speed of price-gains ranking. Another means of further contemplation is offered by how often speedy price trips have been found to be available. That may be helped by the map of Figure 3.
The orientation of this map is like that of the Reward~Risk Tradeoffs in Figure 1; good is down and to the right, not-so is up and to the left. Items in the white Payoffs area at left have achieved average Win Odds amounts less than 80 out of 100, and those in the extreme upper left corner also may have had negative % payoffs from prior forecasts at current RI-levels.
For reference we include SPY at  to provide a sense of market aggregate opportunity and achievement. It turns out that better current combination of Odds and Payoffs are shared by RHT at  and by ADBE and BLKB at . Small sample-size eliminates RHT and BLKB from consideration, though.
But larger or equal-size Realized Payoff probabilities (vertical scale) for Autodesk, Inc. (ADSK) at  and Tyler Technologies (TYL) at [ 1 ] justify their consideration along with ADBE.
One further comparative measure which may be helpful for the individual investor to match up between stock choices and personal preferences is available in the form of our Credibility Ratio, shown in column [N] of Figure 2.
It measures the Upside price change prospect [E] of each stock’s current forecast against what net price gain payoffs [ I ] were actually achieved by prior forecasts like this one. Some, like TYL with a ratio of .92, or the average of the population’s ten best-odds securities of .95, are quite credible.
Generally we like to see Cred.Ratios above .75 as a minimum of reliability. Attention-getting extreme implied forecasts sometimes can appear which may not be intentional, but may simply be the product of bad data entry or flawed communication, or are of an unlikely-to-be repeated market-pro error in pricing at the point of setting terms of the hedge deal.
Looking at Figure 2 points out a less encouraging Cred.Ratio of only .56 for ADBE and a marginal one of .70 for ADSK. But their net Realized Payoffs in [ I ] are both in good double-digit amounts, with triple-digit CAGRs [K]. Calculated from the realized outcomes rather than the forecasts, as are the [N] bp/day numbers, they represent way above-average prospects. Your trade-off choices?
The role of recent history
Visual influences are important to many investors as decision aids. Unfortunately, they are often taken as encouragement for continued holding of now-pricey securities which have recently done well, or discouragement for continuing to hold those recently not doing well, rather than focusing on what may be coming next. We believe that price history pictures are most useful in considering the potential for change in recent past trends.
We typically are most interested where knowledgeable sources make forecasts suggesting trend changes independent of the pictures' past history, since the usual public interpretation of the pictures often provides a source of either supply or demand for the security. Sources which should make the fresh decision easier to implement.
Here are recent-history pictures of FORECAST price ranges for the top-ranked software stocks being discussed. Each one repeats much (but not all) of its data previously presented in Figure 2.
In the month since our last Software Stocks review ADBE stock has dropped in price by 9% but its upside potential by less than half that. Its Range Index, formerly 43, is now 23 and its Win Odds have risen from 82 to 100. Realized gains from the lower RI doubled from 5.5% to 11.1%. Quicker sell target realizations pushed basis points per day up from 7.6 to 30.8. Exciting.
ADSK, like many stocks, has also declined a bit in price, but its upside price expectations have held up well, making it a more competitive investment candidate in its group. At a Range Index of 21 instead of its former 26, its Win Odds increased from 74 to 88 and its Realized payoffs from 7.6% to 13.8%. Quicker profit-taking sell targets boosted the historical bp/day of 8.1 to now an average of 28.4.
TYL’s price decline from its August high is more dramatic and potentially concerning on a six-month daily price range forecast basis. But on a longer, 2-year picture of daily forecasts shown on a one-a-week basis, (left picture of Figure 6) a broader perspective is gained.
TYL at $186 is well above its low recovery turning point of ~$145 in December of 2016. It is now starting to show the kind of repeating forecasts (almost entirely upwards from the heavy dots of its current market quotes) resulting in Range Indexes of negative- to positive single-digit numbers, that were seen back in late 2016.
The left picture of Figure 6 gets updated on Thursdays, and because of Thanksgiving now only shows what it did two weeks earlier. That picture's right-most vertical line entry when updated will show data now contained in the most recent right-hand chart, extending a firming appearance. Encouraging.
The decision, if a single security selection is to be made between Adobe, Inc. (ADBE), Tyler Technologies (TYL), or Autodesk Inc. (ADSK), may be largely influenced by the investor’s personal preferences. Otherwise, multiple choices among any or all of the three should make significant wealth-building contributions to most equity portfolios.
Disclaimer: Peter Way and generations of the Way Family are long-term providers of perspective information, earlier helping professional investors and now individual investors, discriminate between wealth-building opportunities in individual stocks and ETFs. We do not manage money for others outside of the family but do provide pro bono consulting for a limited number of not-for-profit organizations.
We firmly believe investors need to maintain skin in their game by actively initiating commitment choices of capital and time investments in their personal portfolios. So our information presents for D-I-Y investor guidance what the arguably best-informed professional investors are thinking. Their insights, revealed through their own self-protective hedging actions, tell what they believe is most likely to happen to the prices of specific issues in coming weeks and months. Evidences of how such prior forecasts have worked out are routinely provided.
Disclosure: I/we have no positions in any stocks mentioned, but may initiate a long position in TYL over the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.