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price excursions

I have chosen COO as an example because it has other lessons to teach. Note the lines labelled "48% above S2". What we have   done here is to ask the question "how high did the previous bull leg (the one peaking near a cumulative volume = 100) go when   expressed as a percentage above its secondary support (S2)"? This turned out to be 48%. We then apply the same percentage (what I call the "greed factor") to the S2 for the next leg to obtain a (moving) price target. Sure enough, the peak of the next leg occurs where anticipated, although I hasten to add that the agreement is seldom this precise!

We are exploiting the circumstance that successive bull moves are frequently self-similar when viewed in the context of the S/R   hierarchy. Thus, if price excursions are measured relative to the theoretical support levels, different bull moves can be directly   compared notwithstanding the fact that they may occur over vastly different scales of cumulative volume.

To pursue this point further, in the second figure we present a magnified view of the bull move peaking near cumvol=100. Plotted   on the figure is a fourfold hierarchy of support levels and the primary resistance level launched at the peak. The important point to   note is that although we are only dealing with 54 days of data (between cumvol= 70 and 125), there is nevertheless exhibited the   same hierarchal structure that one finds in charts extending over several years. In other words, the zigzags in price behavior that   one observes on short time scales have the same structure (in S/R hierarchal terms) as that seen on long time scales.

The foregoing properties of self-similarity and scale independence are characteristics of fractal behavior. The fractal nature of   stock price fluctuations has been recognized for some time on purely empirical grounds. What has been missing is an   understanding of why markets should behave fractallly (i.e. beyond the obvious fact that they are complex non-linear dynamic   systems). In the Midas method, we have seen that the complex zigzags in price behavior can be (to quote article#8) "understood   with respect to a single algorithmic prescription: support (or resistance) will be found at the volume- weighted average price taken   over an interval subsequent to a reversal in trend". The psychological elements of greed and fear, whose quantification led to   this   algorithm, apply to investors/traders across all time scales. (Someone who has held a stock at a loss for three years is just as eager   to "get out even" as the day trader who is holding a losing position). There is even a more remarkable method of predicting tops   (and bottoms) in the Midas bag of tricks - the so-called TOPFINDER algorithm. Don't miss the next article!