Foundation of Technical Trading: What Makes a Chart Tradable?

The Foundation of Technical Trading
There is an abundance of information on price charts, technical methods, indicators, and various tools. However, the required first step is to understand basic market structure. Without this foundational knowledge, technical applications risk becoming inconsistent and disconnected from broader market behavior.

It is also important to question whether technical charts and tools are effective at all. What makes the market responsive to a trendline, a pattern, or an indicator? And why, at other times, do these tools seem entirely irrelevant? Is the market random? If certain events are predictable, under what conditions can such occurrences be expected?

Experiment: Random Charts

Here is an illustration of four charts; two showing real price data and two randomly generated. While some visual distortion gives away subtle differences, there are more refined methods to construct this experiment that makes telling the difference between real and random almost impossible.

All these charts show viable patterns and possible applications. When presented with these, even experienced people tend to construct narratives, whether or not structure is present. This raises a fundamental question; how can one distinguish real occurrences from coincidental formations on a chart? In case all movements are considered random, then this should indicate that applied methods perform no better than coincidence?

Bias and Distortion
It’s also important to comprehend the influence our perception. As humans we are wired to find patterns, even in random data, which can lead to various cognitive biases that distort our interpretation. For example, confirmation bias may lead us to focus only on evidence that supports our expectations, while apophenia causes us to see patterns where none exist. Similarly, hindsight bias can trick us into believing past patterns were obvious, which can develop overconfidence in future decisions. Awareness of these biases allows us to approach technical tools and charts with greater objectivity, with more focus on probabilistic methods and calculated risks.

Experiment: Random Levels
Perform the following experiment; open a chart and hide the price data. Then draw a few horizontal lines at random levels.


Then reveal the price again. You’ll notice that price can touch or reverse near these lines, as if they were relevant levels.


The same thing can happen with various indicators and tools. This experiment shows how easy it is to find confluence by chance. It also raises an important question, is your equipment and approach to the markets more reliable than random?

Market Disorder
Financial markets consist of various participants including banks, funds, traders and algorithmic systems. These participants operate with different objectives and across multiple timeframes resulting in a wide range of interpretations of market behavior. Trades are executed for various reasons such as speculation, hedging, rebalancing, liquidation or automation; directional intent could be unclear. For instance, the prior may serve to offset exposure, and portfolio rebalancing could require the execution of large orders without directional intent.

Technical and chart-based trading likely makes up a minor segment of the overall market; even within this subset, there is considerable variation in perception and interpretation. There could be differences in timeframe, reference points, pattern relevance and responses to similar information. The market is broader, more complex and less definitive than it appears. The point is that markets contain a high degree of structural disorder, which means most assumptions should be questioned and perceived as estimative.


The effect of buying and selling pressure on multiple timeframes sets the foundation for oscillation in price movements, rather than linear and monotonic movements. This pattern of rising and falling in a series of waves sets the points for where the current structure transitions between balance and imbalance. An overall equilibrium between buying and selling pressure results in consolidative price movement, whereas dominance leads to trending or progressive movement.

Volatility Distribution
To answer the main question: What differentiates real market behavior and charts from random data, and ultimately makes it tradable, is the distribution of volatility. This forms the basis for the phenomenon of volatility clustering, where periods of high volatility tend to follow high volatility, and low volatility follows low volatility. It is rare for the market to shift into a volatile state and then immediately revert to inactivity without some degree of persistence. Research supports the presence of this volatility persistence, though with the important caveat that it does not imply directional intent.

Volatility Cycles
These phases tend to occur in alternation, known as volatility cycles, which set the foundation for tradable price structures. This sequence consists of a contractive phase, marked by compression in price movements, followed by an expansive phase, characterized by increased volatility and directional movement. The alternation reflects shifts in underlying buying and selling pressure. This behavior offers a practical approach to interpret market behavior. A more detailed explanation of the concept could be explored in a future post.


Conclusion
While the idea of profitability through technical trading is often questioned, it remains a viable approach when based on sound principles. The edges available to the average trader are smaller and less frequent than commonly presumed. The concepts of volatility and the ability to locate areas of imbalance forms the basis for identifying conditions where market behavior becomes less random and more structured. This sets the foundation for developing technical edges.

The content in this post is adapted from the book The Art of Technical Trading for educational purposes.