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BASIC STEPS OF THE ALGORITHM

We are now ready to define the basic steps of an algorithm that can identify triangular formations in daily charts. In Figure 4 there is a hypothetical daily closing price of an equity, shown in black. (Refer to this figure for illustrations of the steps of the algorithm.) First, we locate the last two legs of the zz(20%) indicator. The term bending for the zigzag indicator means an apex, defined by two swings of this indicator:

STEP 1: Locate the last point of zz(20%) and label it Р“. Locate the last bending of zz(20%) before Р“ and label it Р’. Locate the last bending of zz(20%) before Р’ and label it A. In the sequence, we produce a linear regression line of the closing price for the time period of the last leg Р’Р“ and we produce the Up and Down indicators for this time span:

STEP 2: Generate a linear regression line for the time period that the leg Р’Р“ lasts and name it reg. Generate the Up and Down indicators of the closing price based on reg for this period. In step 3, we calculate the percentage of the retracement that took place during the period of the last leg of zz(20%):

STEP 3: Let CAand CB be the closing prices at points A and B, respectively, and let РЎ be the indicator of closing prices. Define the height of the formation as the maximum value of the indicator during Р’Р“. (Note: | x | symbolizes the absolute value of x.)

FIGURE 4: THE BASIC STEPS OF THE RECOGNITION METHOD. The black contour line is the closing price of an equity, the green crooked line is the zz(20%) indicator, the cyan line segment is the reg indicator, and the red contour line is the five-period simple moving average of closing price.

The percent retracement produced by the formation is then defined as:

In step 4, we try to evaluate the small swings (SS) of the market inside the formation. Since we don't know the duration of the formation, we shall use the number of crossings of the five-period simple moving average of the closing price through the regression line for the time period of Р’Р“: STEP 4: Define the SS number to be the number of crossings of the five-period simple moving average of closing price through the regression line during the time span of Р’Р“.

The first condition a triangular formation must satisfy is the balancing of supply and demand forces leading the market to an equilibrium point. This can be mathematically expressed by stating that the slope of the regression line of the Up indicator is negative and the slope of the regression line of the Down indicator is positive.

The second condition deals with the time period of the formation. The time period of a triangular formation should be at least two weeks (10 trading days) and preferably no more than three months (60 trading days).

The third condition has to do with the market swings inside the formation. We demand a minimum of three crossings of the five-period simple moving average of closing price through the regression line for the time span of Р’Р“. The fourth condition deals with the maximum retracement produced by the triangular formation.

As stated at the beginning of this article, we are mainly interested in triangular formations that occur after strong trends, so there will be ample room for free upward or downward movement after the completion of the formation. I shall allow the triangular formation to produce a maximum retracement of 50%.

STEP 5: The market movement between points Р’ and Р“ is identified as a triangular formation (TF) when all of the conditions below are satisfied:

ў The slope of the linear regression line of the Up indicator is negative and the slope of the linear regression line of the Down indicator is positive.

ў The time span between points Р’ and Р“ is between 10 and 60 trading days.

ў SS

ў %retr>=50

If you want the algorithm to identify longer TFs, you may modify the second condition accordingly. In addition, you may change the fourth condition if you want to be aware of TFs that produce retracements of more than 50%. Using these steps, we can create an algorithm to identify triangular market behavior. Any formation identified as TF is important.