Cycle Analysis [Video]
In the video below, I’d like to outline the study of cycle analysis to make better informed decisions. This analysis is carried out by a software developed by Lars Von Thienen called Cycle Scanner. These views are routinely updated via my mentor room.
Lars: “Knowing how to use cyclical analysis should be part of any serious trading approach and can increase the probability of successful strategies. Because if a rhythmic oscillation is fairly regular and lasts for a sufficiently long time, it cannot be the result of chance. And the more predictable it becomes. There is often a lack of simple, user-friendly applications to put this theory into practice.”
Cycle Analysis Explained
The following chart, courtesy of www.whentotrade.com , summarizes all relevant parameters related to a “perfect” sinewave cycle:
Cycle Analysis: The Calculation Logic
While there is no fix approach to the selection of market rhythms through time-based cycles, I tend to add more weight to lengthier periods as these are the ones that validate the long term dominant flows. Periods below 50 may add unnecessary noise to the main cycles at play. I then combine large length periods with the ones exhibiting the highest amplitude cycles. What I’m doing is picking 1-3 high amplitude cycles in order to create a composite cycle (in magenta line) and then investigate whether or not the standalone dominant cycle can fit this curve.
I then play around with the combination of high amplitude cycles until I get a composite curve that has peaks and troughs that match the price data. In the majority of times, over 80%, I end up finding a combination that matches the peaks & troughs pretty well. If a sufficient in-sample over the last year or so see the peaks and valleys match nicely for the past year, that’s the goldilocks scenario. If not, I play around with different combinations of the high amplitude readings to get the composite curve as close to the price peaks & valleys as I can.
NASDAQ 100 – When Technicals & Cyclical Rhythm Converge
In this category, I provide an example of a market exhibiting an acute directional skew based on the convergence of cycles.
I recently posted the following analysis:
“The Nasdaq composite is starting to look more constructive as a new week starts. Let’s look at the different categories to make an informed study of the context we find ourselves. First off, the structures in the daily and 8h (session by session flows) have turned bullish. The FT (Fractals) indicator exhibits this turnaround. The momentum derived off a 13 period ma has too signaled bears no longer in control. That must be reconciled with the daily momentum still anchored to the bearish side. Overall, 3 out of 4 metrics bullish here. Let’s keep adding information. The most relevant SR has been cleared. If market makers are to draw the floor higher, you’d expect buyside pressure starting to overwhelm sellers to potentially transition into a higher range (13,400-13,700). Besides, the breakout of this SR came after a major mark up thru a clean and commanding bullish candle. This tends to spook sellers trading straight back into this momentum.”
By decoding the most probable cycles based off time, it’s interesting to notice the huge converge through multiple long-term periods. The exhibit bellow illustrates this ideal cyclical environment. Both, a 321 and 164 length, each with a strong amplitude, alongside a very high accuracy rate (bartel) predicting previous turning points, are all converging, Even the 126, when added, strengthens this findings.
I therefore concluded that the path of least resistance near term looked skewed towards the bullish side. Ever since the call in the Global Prime Discord room, the NASDAQ 100 is up over 2%. Sellers wiped with a solid rotation back up. Key now is for the price to poke its heads above the 1.7k-1.75k vicinity with various candles accepting above. This would solidify the outlook for an eventual return to ATHs.
As a final note, this article was intended to outline the importance of cycles in financial markets. If we are able to recognize the dominant cycle by combining both objective data analytics and slight calibrations to best fit the recent rhythmic patterns, we are able to project and better predict behavior into the future. This cyclicality in markets must then be combined with technicals as the ultimate signal.