I go on my series of articles, devoted to Gann’s studies.
In the previous articles, I described how to identify the key dates and price levels for the long-term, middle-term and short-term trading horizon. I also explained how to identify favourite price angle and make forecasts, using grid, and combine them with common indicators.
Before you go on reading, I suggest those, who are unfamiliar with the previous articles devoted to William , read these articles first:
Unknown Method: Square of 9
Unknown Method: Square of 9 (part 2)
Unknown Method: Square of 9 (part 3)
The way to identify key dates and price levels, described in those posts, may seem to be quite complicated and subjective.
For such people, offers an alternative method to apply the Square, which I’ll describe below. Before we start, I want to say that many elements of this method are the same as the steps, I’ve already described. That is why I won’t repeat myself and write about them again. So, if you haven't yet read the previous posts, I recommend you to get familiar with the last three articles to understand the present material.
As an introduction, I’d like to add that the alternative method is neither better nor worse than the previously described one; it is just a little different. Nevertheless, as , himself, recommended, and the experience shows, the best way is to apply all Gann’s tools when you analyze the market and pay special attention to the levels that are identified by both methods.
First, I’ll describe the alternative way to identify key dates by means of Chronometer, the circle that surrounds Square of 9.
How to identify key dates, using Chronometer
In the first part of this educational block, I’ve already mentioned a similar method that identified global in long-term analysis of time periods.
I’ll remind you that the points were identified when I chose the figure that would cross by its diagonal lines the maximum number of the key levels, suggested by Square of 9, marked at the square itself.
To apply the present method, I’ll look for key dates, regardless of the periods of equinoxes and solstices, taking only historical values into account.
First, I should identify the historical high in the price chart of the analyzed instrument. In my case, it is Bitcoin price chart.
As you see from BTCUSD price chart above, Bitcoin all-time high 19666 USD was recorded on December, 2017. I also mark the price low, nearest to that date; it is 5920 USD on February 6, 2018.
Next, I configure Gannzilla settings as I described in the first part.
I use the date of the high as a reference point. Then, I select the figure so that one of its angles must point to this date (see the example in the chart above). Furthermore, the perfect figure will be the one, whose next angle in a clockwise direction coincides with the low marked below, with the deviation of not more than 2-3 days. If there isn’t such a figure, then you need to take the next low and choose the figure, based on it.
You try all the figures, from a decagon to a triangle.
Choose the appropriate figure. In my example, it is a heptagon.(at here)
As it is clear from the picture above, the figure exactly matches to the low of February 6, and so, that is what I need.
Next, I attach all the levels to the dates in the chart, which are marked by the rest of the figure angles on the Chronograph.
As you see from the chart above, all points are quite close to the chart extremes. If the historical high was later than a year ago, all the levels you’ve marked will completely coincide with the chart history. To figure out the historical points for the forecast, I need to mark these points in the future.
To do it, I repeat the circle and mark the same values in the future.
So, I extend the market cycles into the future. This cycle is relevant until there is a new all-time high. In this case, the cycle will start from the new high. I want to emphasize that, according to this method, there are no concepts like long-term or short-term forecasts. You operate only with historical data in the .
The next big stage is identifying the historical price levels. This step is similar to that, described in the second article of the block, devoted to model. So, I need to go back to the chart, where I have already marked the historical values.
As the price favorite level, I mark the one that coincides with date, nearest to today; it must match to the market reversal as accurately as possible. As you see from the chart above, this line is the red line on September 4. At the next step, I need to identify the increment; the price unit when it moves from one cell into another in the . With this regard, offers an alternative way by trial and error
I take the historical low as a reference point, and then, I select the increment so that one of the few nearest values in the cell, which is crossed by the price favourite level, was at the extreme that matches to the chosen key date. To explain it more clearly, I'll give an example.
As you see from the chart above, the BTC high in the studied period is at 7411.85 USD. Bitcoin all-time low was 0.003 USD for 1000 BTC in 2009; so, first, I take a possible tick value in chart as 0.01 USD. Next, I need to build price levels from this point with the increment so that one of the cells at the favourite angle is as close to the high at 7411.85 USD as possible.
, as an alternative method to select the starting value of the increment, offers to use the increment of 5 USD and more for the prices higher than 1000 USD; 0.5 USD and more – for the prices exceeding 100 USD. I suggest we make it a little simpler and divide the price of the high into 1000. Experience proves it is one of the most relevant ways.
Therefore, the settings will look like this: (at.here)
By trial and error, I got the increment value at around 7.633 USD. Having found the increment, I can figure out the Square of 9. Besides, I want to emphasize that the square size must be increased so that the last value, matching to the favourite angle, will be higher than the high (in the given example it is 19666 USD). In my example, the square size was increased from 10 cells to 33 cells. You may already know what to do next. You are right; I just mark the crossed price levels at the favourite angle that points to Sep. 4.(at here)
Finally, if you’ve correctly followed my recommendations, you’ll have a similar big square and the diagonal line along the green cells. I marked the high of 7411, which was crossed, by yellow. (at here)
Now, I’m about to start one of the most tedious stages of analysis, when you need to mark all the identified levels in the chart. Fortunately, the historical highs are not updated very often, and so, I won’t have to make these calculations very frequently.
Finally, I have the following picture. You can choose the color and the thickness of the lines as you like. As you see from the chart above, almost all price key levels match to the key points and, in the chart history, they are the zones of reversal, consolidation, or correction in the trend. So, now, there is the most interesting moment. All Gann’s trading models are based on the analysis of cycles. And this method is not an exception. If you want to better understand what I’m writing about, I recommend you to read about analysis. I devoted a whole educational block to models a long time ago.
For ease of the analysis, I marked each level with a number. You may have a different number of levels in your chart. It depends on what level you start from to construct the grid. I take the base level of 1320 USD, as I don’t think Bitcoin will go deeper. Nevertheless, the order number of the level doesn’t matter, as I will be calculating the difference.
As I apply a heptagon to figure out the cycle, the cycle will include seven columns, seven stages that I ranked by using the letters from A to G.
Then, I count the cells, closed during the time of each stage. If the BTCUSD ticker broke through the cell’s line but didn’t cross the block completely, I don’t count this square. There also matters the mathematical sign. It is whether you have the number with the plus sign or the minus. It will further help you identify if the price will go up or down.
It should be also noted that the forecast basically works out only if there is a complete cycle. If the starting point of the new cycle is based on a completely new historical high, for your analysis, you can use the regularities, emerging between the stages; but, if you extend the old cycle into the future for your forecast, you can make a lot of errors.
It is clear from the chart above that during the first stage, it is A, the price went 10 cells down, during the B stage, all the rise finished by the rollback, and the column closed with zero increment. During the next C stage, the growth, adjusted for the loss, covered 2 cells. During the D stage, Bitcoin was two cells down.
At the E stage, it was 1 cell up.
At F stage it was one more cell down.
At G stage, the fall covered four cells.
Next, I draw the cycle projection in the chart. The moves are identified according to how the previous cycle stage finished; therefore, after each of the stages finishes, I correct the expectations for the next one. Nevertheless, the direction of the movement inside the stage can be anticipated quite accurately.
As you see, a particular increase or reduction in the cells’ number for the projection into the future can’t be taken literally. It is about a relative change. That is, if the previous cycle featured the fall by 1 cell, and the next one was 2 cells down; therefore, next year, if the price goes down by two cells in the same stage, it should rise by four cells in the next stage; that is proportion is the same for the number of cells between the stages and the direction of the movement. In addition, there are no strict constraints, it rather about the price movement direction and the minimum potential for the movement inside the stage.
For example, I’ll make a forecast for the Bitcoin current situation. Assume that the last G stage of the cycle finished with a fall by four blocks. Taking into account that in the past, the A stage featured a fall by 10 cells, following the rise by 11 cells, then I don’t expect that the price will go up in the future A stage higher than movement length in the previous G stage, which is most likely to close by adding three cells up. It doesn’t mean that the price can’t at all add 6 cells up. I just understand that this stage is highly likely to feature a rollback and see the minimum target for it.
At the next B stage, the increment is equal to zero, and so, there can be both the rise and the fall, it is only important that it is likely to finish at breaking even. As an example, I displayed different possible scenarios by the dotted lines in the chart above.
Next, at the C stage, Bitcoin is likely to draw down a little, based on the idea that I mirror the previous cycle.
If the next stage closes with the price increase, the mirror effect will disappear, as the cycle may enter the phase and the price will start a new fall, despite that it was growing before. Before I finish the post, I want to again emphasize that the above chart doesn’t display my forecast for Bitcoin future price; it is just an example of how you can apply the Square of 9 to forecast the price moves in each stage of the cycle. Here, it is very important to pay attention to how the previous stage finished. What is the final price change, compared to the previous stage? What is the price change, compared to the same stage in the previous cycle?
To exploit this method most efficiently, I recommend combining it with other Gann’s trading methods, including those, described in the previous articles. In the next post, I’ll move away from mathematics and write about the stars. I’ll describe how used astrology in his studies and try to apply it in practice.
Here, I am about to finish another article, devoted to Delbert William and his studies, which I applied to the BTCUSD pair. I hope this information is interesting and useful for you.
I wish you good luck and good profits!
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