Probabilistic RealmI remember taking the CMT exam, where one question referenced the Efficient Market Hypothesis (EMH), which asserts that price action is purely random. To avoid losing points, I had to select “random” as the correct answer, despite knowing that market behavior is far more structured than EMH suggests. Despite of passing I still won't ever agree that market is random.
Prices are neither random nor deterministic. Market fluctuations follow a chaotic structure, but chaos is not the same as randomness. Chaos operates within underlying patterns and scaling, whereas randomness lacks any order or predictability. Although chaos makes predictions difficult, keep in mind that the universe is not random— effects still follow causes in continuity . No matter how chaotic a system may seem, it always follows a trajectory toward a certain point.
For example, in Lorenz’s model of chaos, the trajectory formed a pattern resembling the wings of a butterfly. Understanding these patterns of chaos has practical applications. In the market, even a slight fluctuation can trigger irreversible changes, reinforcing the idea that we cannot rely on absolute forecasts— only probabilities .
The market is not necessarily a reflection of the economy; rather, it reflects participants’ feelings about the “economy.” The human emotional component drives the uncertainty and chaos, making it essential to visualize price dynamics exclusively through "systematic" lens.
Market Structure Is Self-Referential
Markets move in proportion to their own size, not in fixed amounts. Price is arbitrary, but percentage is universal – A $10 move on Bitcoin at $100 is not the same as a $10 move at $100,000. Percentage metrics reflects this natural scaling and allows comparability across assets and timeframes – A 50% swing in 2011 holds similar structural significance to a 50% swing in 2024, despite price differences. Using log scale is a must in unified fractal analysis.
Percentage swings quantify the intensity of collective emotions—fear, panic, euphoria—within market cycles. Since markets are driven by crowd psychology, percentage changes act as a unit of measurement for emotional extremes rather than just price fluctuations. After all it's the % that make people worry..
The magnitude of percentage swings encodes emotional energy, shaping the complexity of future market behavior. This means that larger past emotional extremes leave deeper imprints on market structure, influencing the trajectories future trends.
The inverse relationship between liquidity and psychology of masses partially explains the market’s fractured movements leading to reversals. In bullish trends, abundant liquidity fosters structured price behavior, allowing trends to develop smoothly. In contrast, during bearish conditions, fear-driven liquidity contraction disrupts market stability, resulting in erratic price swings. This dynamic highlights how shifting sentiment can amplify price distortions, causing reactions that are often disproportionate to fundamental changes.
PROBABILISTIC REALM
Rather than viewing fluctuations as a sequence of independent events, price action unfolds as a probabilistic wave shaped by market emotions. Each oscillation (outcome) is relative to historical complexity, revealing the deep interconnectedness of the entire chart that embodies the “2-Polar Gravity of Prices.”
Fibonacci numbers found in the Mandelbrot set emphasizes a concept of order in chaos. The golden ratio (Phi) acts as a universal constant, imposing order on what appears to be a chaotic. This maintains fractal coherence across all scales, proving that price movements do not follow arbitrary patterns but instead move relative to historic rhythm.
The reason why I occasionally have been referring to concepts from Quantum Mechanics because it best illustrates the wave of probability and probabilistic realm of chaos in general. Particularly the Schrodinger's wave equation that shows probability distributions. Key intersections in Fibonacci-based structures function as "quantum" nodes, areas of market confluence where probability densities increase. These intersections act as attractors or (and) repellers, influencing price movement based on liquidity and market sentiment. Similar to Probability Distribution in QM.
Intersections of Fibonacci channels reveal the superposition of real psychological levels, where collective market perception aligns with structural price dynamics. These points act as probabilistic zones where traders’ decisions converge, influencing reversals, breakouts, or trend continuations. Don’t expect an immediate reversal at a Fibonacci level—expect probability of reversal to increase with each crossing.
To prove that Efficient Market Hypothesis is wrong about prices being random, I'd go back to a very distant past from current times. For example, price fell 93% from 2011 ATH, reversed and established 2013 ATH.
Using a tool "Fibonacci Channels" to interconnect those 3 coordinates reveals that markets move within its fractal-based timing derived from direction.
If prices were random, this would have never happened.
The bottomline is that viewing current price relative to history is crucial because markets operate within a structured, evolving framework where proportions of past movements shape future probabilities. Price action is not isolated—it emerges from a continuous interaction between historical trends as phases of cycles, and liquidity shifts. By analyzing price within its full historical context , we can differentiate between temporary fluctuations and meaningful structural shifts justified by the fractal hierarchy. This approach helps identify whether price is expanding, contracting, or aligning with larger fractal cycles. Without referencing historical complexity, there is a risk misinterpreting patterns from regular TA, overreacting to short-term noise, and overlooking the deeper probabilistic structure that governs price behavior.
