SP500 ETF: Fibonacci Mapping

As you may know, Williams Fractals indicator identifies potential reversal points by marking a high (or low) surrounded by two lower highs (or higher lows) on each side, forming a five-bar pattern that signals possible turning points in price. Unfortunately, the simplicity of such indicator provides just tiny perspective, undermining broad implication of the concept.

Before I begin diving into processing geometric narrative of emerging price via fibonacci channels, I want to explain how I interpret fractals.

When I use the term "fractal", I'm not just talking about the points alone. Market continuously corrects itself, so analyzing it by price alone can bring more confusion than help. The object of observation shouldn't be limited to quantifying just by a single property. Chaos by default requires awareness from both price and time aspects. The easiest way to root it in my vision was through realization that price is a function of trading time intervals. Its activity can be described as cyclical progression, as if it is wired by multiple "springs" of different tensions.
Classic TA patterns known to literally anyone are great for anticipating a move in surface level forecasts. Since my line of work focuses on prediction over forecasts, it requires deeper structural awareness behind complex oscillations.

Let's observe the way selloff scales from ATH and how it impacts fractal hierarchy.

The first corrective bullish wave can be explained as a reaction to initial impulsive bearish wave. The bigger scale drop from ATH to a lower point explains why the corrective bullish wave looks the way it is. And so on:
In fractals, scaling laws describe how key properties change with size, typically following power-law relationships that reflect the structure’s self-similarity, where a characteristic scales with the size raised to an exponent.
To build a probabilistic model, we must keep in mind how the smaller bits make up bigger scale picture. ATH, established bottom and angle of progression defined by pullback highs, all those points have structural weight. Since psychology of masses that shapes price dynamics is governed by mathematical sequences found in nature, it's fair to use Fibonacci Channels to map the geometry of interconnectedness.
Similarly, all of those points can be referred by another fibonacci channel with opposite direction.

From my perspective, traditional TA patterns reflect just phases of cycle, this is why I unify those fragments into broader scalable shapes. This distinctive branch of Fractal Analysis allows to track systematic aspects of market behavior and explains how a pattern replicates itself in rhythmic continuity.