We speak here about repetitive activity within areas of congestion.
“Congestion action†is our term for that kind of trading which goes up and down, up and down, between support and resistance, and resistance and support. This pattern occurs again and again, and occurs in a great majority of all market activity. When you see the market bouncing back and forth across the PLdot without closing three times in a row on one side – that’s congestion action.
Certainly congestion action does take up a huge percentage of market activity if we include the kind of congestion action that we see in very slow trends up or down, when the whole congestion area itself is slowly on the move.
These slowly rising or falling congestion areas are true congestions in our view, because they never develop into a trend. In the Drummond Geometry methodology, that would only occur – can only occur — when we have three consecutive closes in a row on one side of the PLdot.
However you cut it, one thing must be clear. Congestion action is the essence of normality. It is normal, normal, normal, as commonplace as brushing your teeth, or washing your hands, or walking about.
One might suppose there are implications to this fact, and one would be right.
Normal does not mean identical, because the normal encompasses infinite variety.
Look at any common element in nature – say the leaves on a shagbark hickory, or the tines on white-tailed deer antlers. You could collect a hundred thousand leaves, and not find one that was identical to another. Yet if you were to chart out the nature of the differences you would find that the patterns of the leaves fell perfectly within the known laws of statistical variation and commonality.
Now deer antlers are interesting phenomena. (What on earth do deer antlers have to do with trading, you are perhaps asking?) They clearly grow in a regular pattern, as we see two antlers per stag head, usually, and they seem to branch in similar ways. But these appendages also have enormous variety. And they grow larger each year, usually in the same pattern for each deer, but not always…
Some of the ways that they vary – thickness, number of tines, outside spread side to side, height, inside spread, number of tines up or tines down, the way the antlers split and branch, close to the head or higher up in the tree. The variety can be caused by age, diet, by stress, accident and by heredity and shifts in the gene pool, in short by this and by that.
Hunters and collectors have an interest in seeing who can come up with the largest set of antlers, but there are so many different variations that they have to establish a special way of measuring the difference between the antler sets. That way they can settle the arguments that inevitable arise between the hunter who has the deer antlers that spread especially wide and the hunter whose antler set spreads not so wide but has more tines, and so forth.
Well it turns out that there is a special set of combined measurements that, when taken as a set, combine all of these many variations and establish a single number which encompasses all of the variety into a simple way of ensuring and comparing these differing antlers. It’s called the Boone and Crockett score, a combined total of beam, tine, and spread, all measured out to the eighth of an inch.
All this is a complicated way of explaining that sometimes we have to develop a sophisticated way of measuring normality so that we can also establish the outer limits of what occurs in nature. In the Drummond Geometry methodology we do this through our definitions of congestion and congestion action, the five kinds of trading. And then we add the monitoring tools so that we have a complete methodology of establishing the normal and the not so normal.
Normal does mean commonplace, and thus predictable, but only in a certain way, and only in groups and samples and selections, not in specific cases. Most leaves are symmetrical, but there are those anomalies that are not. Most deer have matching antlers on both sides, but some do not, and in any case the word ‘matching’ implies precisely identical, and that does not occur, for there are always small variations, one side to the other.
So “The Normal†is a matter of definition, of “screeningâ€Â, or â€Âgraining,†as in the “coarse graining†and “fine graining†we spoke of earlier in these lessons.
Where do we draw the line? If we include all the outlying points – the distant and aberrant data points — then we would have no difference between the normal and the abnormal.
The Normal requires a definition of a range, and this is the business of statistics.
We run across the concept many times in many different types of market analyses. Statisticians often measure normality by measuring the degree to which an individual value in a probability distribution tends to vary from the mean of the distribution. This is called the standard deviation, and probability can be measured in terms of the number of standard deviations. About 68 percent fall within the first standard deviation, 97 percent within the second standard deviation, and so forth. These concepts have been known and studied for centuries.
But the critical point here is that one cannot predict the placement of any single data point. One can not predict the outcome of any single trade but you can predict the percentage outcome of many trades.
Trading is a game of percentages. One cannot predict everything and so there will be losses, and one must learn how to take these losses, and control them. But if the trading plan is sound there will be many more wins than losses, and that is where the potential for winning comes in.
Let’s think about variation and constancy in the natural world.
This is normality, in its infinite variety. Apply the right “screen†or “filter†and you can see clearly what is occurring.
So normality is a matter of probability and percentages. A moment’s thought and you must realize that the obverse is also true – that the aberrant, the abnormal, and the occasional are also a matter of percentages. It’s just that the percentage is much smaller.
Virtually all scientists and social scientists are completely at ease with these concepts. It is familiar material in many fields.
Let’s think about the practice of medicine for a moment. A patient comes in to the physician’s office with this or that complaint and the physician has to figure out what might be causing the symptom. After all, many complaints are vague and could result from many different conditions. The physician has to take all of his knowledge and the sum total of his past observations and make an educated guess, based upon the percentages. A child comes in with a sore spot on his leg. Chances are it is a bruise, not bone cancer. A woman with a stressful job gets headaches. Probably stress as opposed to a fractured skull. An overweight middle-aged man presents with a nagging painful spot by his sternum after eating. Chances are it is heartburn as opposed to a heart attack. But in order to make the diagnosis, the physician has to know what it could be as well as what it likely is. Oft-times the difference between the experienced physician and the rank beginning medical student is that the young student leans towards the extreme in diagnosis because all the possibilities for exotic or statistically improbably actions are much more attractive to him than the commonplace condition.
Physicians have a saying for this, “When you hear hooves, you think of horses, not zebras.â€Â
To apply all this to the art of trading? Well, it is not a big step. Learn to play the percentages, be realistic about what is likely to happen, and while you remain aware about the possibilities of this particular move being a breakout, chances are that you will find that the normal prevails yet once more.
Some games of chance are highly worked out, such as the gambling house games, where the probabilities are known to ten decimal places. Poker, where the probabilities of drawing into a royal flush have been worked out since the seventeenth century, is one example, and so the information is perpetually available to all who will invest the time to learn it.
The idea of the normal has been studied and worked out in detail a series of brilliant mathematical innovations in the seventeenth century that have made the modern science of risk management possible. The whole idea of the futures market is based on shifting risk from one party to another, something what would be impossible if we had no way to measure, describe, or quantify risk. Risk is the underbelly of normality, and when we measure the normal we also have measured risk.
It is for this reason that congestion action trading is so interesting. We can measure the probability of this or that happening with great statistical precision. We can learn how to trade this market condition in such a fashion that we are running with the horses, not zebras.
The normal is about boundaries, and boundaries are about limitations, and trading with limitations means trading with guidelines. Trading – any kind of trading, but especially trading in congestion action – is confusing and troubling when conducted without guidelines. We must give definition to our approach to the market or we will be overcome with confusion. However too many rules create harshness, rebellion, and further confusion, so that there must be limits even on our limits.
In the end, that is the challenge of congestion action trading – to have the right concept of the normal, specified the right scale, the right “graining†for the situation we are encountering. And then we must place this understanding of the normal in the proper context, where we expect and react to things in the excepted way, but in the back of our mind always stay aware of the possibility that this time it could be different.
This might make one think that excessive emphasis is placed on trend following, as it is abnormal, almost an aberration, in a way, except of course it is too glib to say such a thing.
Nevertheless if we learn to understand the market’s normality, then we shall have the opportunity to tap this normality and turn it to our own purposes, and to create wealth, and if we are wise, to create freedom with that wealth.
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