The recursion in Chan theory has clear definitions at every stage in the original text, but this does not prevent the situation where 'everyone has their own interpretation'. Since its creation, Chan theory has gone through more than a decade of development. Currently, whether in QQ groups, Zhihu articles, or any offline location, discussions involving the classification of Chan theory will inevitably and immediately lead to various differing opinions. The situation of 'thousands of interpretations' has become an objective fact. Without breaking, there is no establishment. After careful consideration, I have created a set of recursive rules that are completely different from the original Chan theory, and there is no room for controversy. Whether a single stone can stir up layers of waves is up to everyone to evaluate.
The key words of this article are five characters: 'Modified Chan Theory Morphology!'
This mainly introduces a set of morphological recursive rules I created, which is completely different from the original morphology of Chan theory. Here is a comparison table of the differences between the two:
The recursive rules of the original Chan theory
The order of morphological recursion in the original Chan theory is: K-line → classification → segment → line segment → lowest level center → lowest level trend type → higher level center → higher level trend type… maximum level center → maximum level trend type.
Each recursive object and recursive rule has a strict definition in the original text, which will not be elaborated here. Below is a focus on a set of morphological rules I have created.
Definition and handling of K-lines
K-lines are the smallest unit of recursion, similar to quantum in physics, indivisible. A K-line has four data points: highest price, lowest price, opening price, and closing price. Here, only two data points are needed: highest price and lowest price, as shown in the figure:
In the above figure, the left side shows the original K-line, and the right side shows the processed K-line. The processed K-line discards the opening and closing price information. Why is this processing necessary? Because overly localized data has a negligible effect on the force of larger structures, almost to the extent that it can be ignored. Therefore, to facilitate the simplicity of recursion without affecting the structural force, ignoring some redundant data is entirely feasible. Thus, the chart generated looks like the figure below:
In actual charting software, the displayed K-lines have both closing and opening prices. However, for structural analysis, these two data points are not very meaningful. This must be clearly understood; otherwise, one may be easily disturbed by unnecessary localized information.
Peak classification and peak, bottom classification and bottom
Definition of peak classification: If the highest price of a K-line is not less than the highest prices of the previous and subsequent K-lines, then the combination of these three K-lines forms a peak classification, with the highest price of the middle K-line constituting the peak.
It is represented in code as: H>=REF(H,1) AND H>=REFX(H,1);
H represents the highest price of the K-line, REF(H,1) represents the highest price of the previous K-line, and REFX(H,1) represents the highest price of the subsequent K-line.
Definition of bottom classification: If the lowest price of a K-line is not greater than the lowest prices of the previous and subsequent K-lines, then the combination of these three K-lines forms a bottom classification, with the lowest price of the middle K-line constituting the bottom.
It is represented in code as: L<=REF(L,1) AND L<=REFX(L,1);
L represents the lowest price of the K-line, REF(L,1) represents the lowest price of the previous K-line, and REFX(L,1) represents the lowest price of the subsequent K-line.
In the definitions above, there is an equal sign, which is different from the classification definition in the original text of Chan theory, as shown in the figure:
The peak and bottom classifications corresponding to the previous two figures occupy most scenarios. There are very few cases, as shown in the right figure, where multiple consecutive K-lines have equal highest prices or lowest prices. An extreme case is when multiple consecutive K-lines have both equal highest and lowest prices. As shown in the figure, this is the case where multiple consecutive K-lines correspond to continuous peaks and bottoms.
It should be noted that in the definition of classification, there is a keyword 'after', indicating 'the next K-line'. This is equivalent to introducing a future function. Therefore, the establishment of the peak of a peak classification and the bottom of a bottom classification needs to be confirmed by the next K-line; at the moment, it is impossible to confirm the establishment of that peak or bottom. This principle extends to trends, meaning that the first type of buy and sell points in any trend cannot be confirmed at the moment; it requires the last structure to be broken for confirmation. This last structure only needs to be broken at a lower level, and even in the framework of a range, a smaller level can be broken to confirm the establishment of the first type of buy and sell points. For example, in the trend type with a segment as the center, the formation of a classification can confirm the establishment of the reversal point, which is the establishment of the first type of buy and sell points in that segment.
Definition of segments
With the definition of classification, the definition of segments can naturally be derived: segments are divided into upward segments and downward segments. An upward segment is formed by connecting a bottom and a peak; a downward segment is formed by connecting a peak and a bottom.
This differs from the definition of segments in the original Chan theory, which requires at least 5 K-lines. Here, there is no such requirement; as long as it meets the criteria for peaks and bottoms, it can be connected into a segment. In the most extreme case, a single K-line can be both a peak and a bottom, thus forming a segment. As shown in the figure:
The above figure shows the real-time chart of the NASDAQ index, with a total of 13 segments. A particularly special case is the 5th segment, which is formed by a single K-line. This may seem strange, but since it is defined this way, we follow the definition to classify it. Such situations are generally rare, and these segments typically correspond to larger amplitude fluctuations. Large fluctuations imply significant energy and force, which cannot be ignored in dynamic analysis, and the direction of the trend is determined by the structural force. This force is either a value of energy that occupies a considerable amount of time or a value of force that occupies a considerable amount of space. Therefore, from a dynamic perspective, forming a segment this way is entirely reasonable.
The 6th segment is an upward segment connected by a bottom and a peak, but there is an ignored bottom classification in between. The reason is that during the upward extension of the previous bottom segment, the peak classification has not yet appeared, while the bottom classification has appeared. A segment cannot connect bottom to bottom but must interleave peak and bottom. Furthermore, this bottom has not created a new low compared to the previous bottom; instead, it has created a new high and formed a peak classification. Hence, this segment needs to extend upward to that peak classification, which is consistent with the processing rules in the original Chan theory.
There are also more special cases, such as when multiple consecutive K-lines have equal highest prices and equal lowest prices, as shown in the figure:
The above figure is a snapshot of the real-time chart of the FTSE A50, with a total of 7 K-lines, labeled with numbers 1-7, producing 7 segments. Why is the ending point of the first segment not 2 but 3? Because 2 is a peak, but there is no bottom after 2 and a new peak 3 emerges, so this segment extends to 3. While 4 is also a peak, why does this segment not extend to 4? Here we need to follow a priority principle: once a peak is formed, the next point must prioritize connecting to a bottom; similarly, once a bottom is formed, the next point must prioritize connecting to a peak. Therefore, after the peak at 3 is established, it must prioritize connecting to the bottom at 4, and when the bottom at 4 is established, the next point must connect to the peak, which happens to be 4 itself. Thus, the upward segment connects to the peak at 4, forming a segment with a single K-line, and the subsequent segment division continues in this manner.
A completely new set of recursive rules
The recursion of 'K-line → classification → segment' has been resolved above. In the recursion of the original Chan theory, recursion to the segment is only the starting point of recursion; segments are followed by line segments, which form the minimum level centers. Centers also have movements such as extension, expansion, and emergence, and they also have upgrades, including two types of upgrades: extending 9 segments and center expansion. Many controversial recursive issues arise here, including segment and center upgrades, especially concerning center upgrade issues. According to the recursive rules, extensions of 9 segments and center expansions require mandatory upgrades. So how to upgrade? What are the three segments to upgrade to? How should each segment be drawn? Where are the starting and ending points for each segment? These questions are highly controversial, and many people, including myself, can easily become confused. Here I design a set of recursive rules with no room for controversy. First, we must understand that our ultimate goal in recursion is to transform trends into line segments. From K-line to segment to line segment to trend, all must be transformed into different levels of segmented line shapes. If this is the case, we only need to design a set of rules and repeatedly connect these line segments. Starting from the most basic segment, it is equivalent to converting multiple K-lines into a single independent line segment. The endpoints connecting the segments are the peaks and bottoms in the classification structure, and the elements forming the classification are K-lines, which is why it is also called K-line classification. According to the definition of K-line classification, if the elements forming the classification are segments, then we will produce segment classifications, as shown in the figure:
The left figure shows the peak classification, while the right figure shows the bottom classification. The elements forming this classification structure can be K-lines or segments. If they are K-lines, the three endpoints of the peak classification correspond to the highest prices of three adjacent K-lines, while the three endpoints of the bottom classification correspond to the lowest prices of three adjacent K-lines. A classification formed by K-lines is called a K-line classification, which includes K-line peak classification and K-line bottom classification. If the endpoints of the classification are formed by the intersection of two adjacent segments, that is, 'upward segment + downward segment' forms the segment peak, and 'downward segment + upward segment' forms the segment bottom, then the classification structure formed by these three continuously similar endpoints is called a segment classification, including segment peak classification and segment bottom classification. Just like the definitions of peaks and bottoms in K-line classifications, the highest point in the segment peak classification is called a peak, and the lowest point in the segment bottom classification is called a bottom. With the definitions of segment peak and bottom classifications, we can further recursively classify the trends. The starting and ending points of the trends are the connections between the peaks and bottoms of adjacent segment classifications, just as the starting and ending points of segments are the connections between the peaks and bottoms of adjacent K-line classifications. This gives us the lowest level of trend types. Similarly, if the endpoints of the classification are formed by the intersection of two adjacent trends, that is, 'upward trend + downward trend' forms the trend peak, and 'downward trend + upward trend' forms the trend bottom, then the classification structure formed by these three continuously similar endpoints is called a trend classification, including trend peak classification and trend bottom classification. Just like the definitions of peaks and bottoms in segment classifications, the highest point in the trend peak classification is called a peak, and the lowest point in the trend bottom classification is called a bottom. With the definitions of trend peak and bottom classifications, we can recursively classify even larger level trends. The rules remain the same; the trend peaks and bottoms of lower levels are connected in sequence, and so on, until all levels of trends are completely recursively classified. Of course, generally speaking, under a fixed period of trend viewing, a software can display approximately 5,000 to 10,000 K-lines, while each level of trend components is roughly between 5-10. Based on this calculation, starting from the segment level, a chart can at most recursively derive 4-5 levels, as shown in the figure:
In the above figure, a total of three levels have been recursively derived, with the lowest level being segments, the second level being segment trend types, and the third level being higher-level trend types. It can be seen that once the segments are drawn, all levels can easily be converted into this linear segmented structure without any controversy. In this recursive process, there is no need to consider the concept of centers, nor do we need to consider issues of level upgrades. Everything is decomposed into line segments starting from the segments according to this simple rule. Then, in the resulting figures from this recursion, we define centers, trend types, and levels. This is completely different from the original Chan theory's approach, where recursion is done through center levels to derive higher levels. A lower-level center must exist before a higher-level trend can emerge. Here, recursion to higher levels does not require centers; everything is drawn according to the rules first, and then we define the centers for each level, reversing the order. For example, suppose there is a chart of a certain level of trend type, and then a phenomenon described in the original Chan theory occurs, such as center expansion or center extension. According to the original Chan theory's rules, one would have to analyze whether the center has been upgraded. However, here, even when a center expansion or center extension of 9 segments occurs, there is no need to consider whether the center has upgraded. Simply follow the rules above to classify, and if three overlapping line segments of higher levels can be drawn, then it is naturally upgraded; otherwise, it is not upgraded. Therefore, from this perspective, whether a center has upgraded is not defined or analyzed but is intuitively drawn. If a higher-level center is drawn, then it has upgraded; if a higher-level center cannot be drawn, it does not upgrade, regardless of how many segments it extends or how it expands. Everything is based on what is visually apparent; it is that simple.
Regarding the definition of the center, this differs from the original Chan theory, and I will publish it separately later.
Did you see that? All trends have been recursively completed from K-lines to the highest level, yet even the definition of the center has not been mentioned. It's so wonderful.
These days I am preparing for the opening of a divine layout!!!
Comment 168, get on board!!!
Impermanence leads to impermanence leads to impermanence!!!
Important things are said three times!!!
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