Academy: Dynamic Cycles Explained
The assumption that cycles are static over time is misleading for trading purposes.
Dominant Dynamic Cycles morph over time because of the nature of inner parameters of length and phase. Active Dominant Cycles do not abruptly jump from one length (e.g., 50) to another (e.g., 120). Typically, one dominant cycle will remain active for a longer period and vary around the core parameters. The “genes” of the cycle in terms of length, phase, and amplitude are not fixed and will morph around the dominant mean parameters.
Steve Puetz, a well known cycle researcher, calles this “Period variability“:
“Period variability – Many natural cycles exhibit considerable variation between repetitions. For instance, the sunspot cycle has an average period of ∼10.75-yr. However, over the past 300 years, individual cycles varied from 9-yr to 14-yr. Many other natural cycles exhibit similar variation around mean periods.” Puetz (2014): in Chaos, Solitons & Fractals
These periodic motions abound both in nature and the man-made world. Examples include a heartbeat or the cyclic movements of planets. Although many real motions are intrinsically repeated, few are perfectly periodic. For example, a walker’s stride frequency may vary, and a heart may beat slower or faster. Once an individual is in a dominant state, the heartbeat cycle will stabilize at an approximate rate of 85 bpm. However, the exact cycle will not stay static at 85 bpm but will vary +/- 10%. The variance is not considered a new heartbeat cycle.
This pattern can be observed in the environment in addition to mathematical equations. Real cyclic motions are not perfectly even; the period varies slightly from one cycle to the next because of changing physical environmental factors. This dynamic behavior is also valid for financial market cycles.
However, anticipating current values for length and cycle offset in real time instead of the mean value is crucial to identifying the next turn. It requires an awareness of the active dominant cycle parameter and requires the ability to verify and track the real current status and dynamic variations that facilitate projection of the next significant event.
The next illustrations show a grey static cycle. The variation dynamic in the cycle is represented by the red one with parameters that morph slightly over time.
Effect 1: Length Shifting
Points from left to right:
A – First Cycle Top; B – Second Cycle Top; C – Third Cycle Top; D – Fourth Cycle Top
Points A and B show an acceptable fit between both cycles. However, the red dynamic cycle has a greater parameter length. The past data reveal that this is not significant, and there is a good fit for the theoretical static and the dynamic cycle at point A and B. Unfortunately, the future projection area on the right side of the chart where trading takes place reflects an increasing deviation between the static and dynamic cycle.
The difference between the static and dynamic cycle at points C and D is now relatively high. Following only the theoretical static cycle will not provide information concerning the next anticipated turning points.
Effect 2: Phase Shifting
Both: Combined Effects
In practice, both effects occur in parallel and change continuously around the core dominant parameters. The deviation in the projection area at points C and D shows that just following the grey static theoretical cycle will rapidly become worthless compared to the red real-world “dynamic”cycle. However, trading takes place at the right side of the chart. Therefore it is important to follow the dynamic nature instead of just “plotting” theoretical cycles on the trading chart.