I’ve been thinking about technical analysis (TA). Not so much how to do it, but more about what it actually is. Some of it can be tested scientifically, but a lot can’t (for more on this distinction refer to the excellent book by David Aronson, “Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals”). So, TA isn’t science, but to therefore conclude it is art seems like giving up and going back to a lazy binary classification.

I found a paper that looks at the topic in an interesting way. “On the Analogy Between Scientific Study of Technical analysis and Ethnopharmacology” by Waldemar Stronka compares TA to folk-medicine. This comparison is interesting.

Ethnopharmacology is the study of traditional or folk remedies. Many of these remedies, initially discovered through trial and error, later became the basis for modern medicines like aspirin and ephedrine. The critical progression in ethnopharmacology, which could also be applied to TA, involves moving through three stages:

1. We know the remedy works: the initial recognition that a certain folk medicine produces results.
2. We know how it works: understanding the underlying mechanisms that make the remedy effective.
3. We can modify it to work better or differently: using this understanding to enhance or adapt the remedy.

In the context of TA, most of the debate among economists and analysts remains stuck on the first point: “Does TA work?” This question, while important, only scratches the surface of what TA could be. Just as trial and error in traditional medicine eventually led to drugs we rely on today, the insights from TA—patterns, indicators, and signals—might hold underlying truths about market behavior that we are just beginning to explore scientifically. It’s entirely plausible that some of the methods used in TA do work, although not always for the reasons that practitioners claim. This alone warrants moving beyond the binary argument of “works or doesn’t” to a more refined discussion on why and how certain elements of TA function.

If we follow the ethnopharmacology analogy, the next logical step would be figuring out the mechanisms behind why some technical indicators work. This could involve connecting TA more firmly to fields like behavioral finance and quantitative analysis. Behavioral finance shows us that markets are driven by psychological forces—fear, greed, and herd behavior, among others—which could explain why certain patterns emerge repeatedly. For instance, the idea of support and resistance levels might reflect psychological price points where market participants are inclined to act, creating self-fulfilling prophecies. Likewise, quantitative analysis can help us refine these insights by subjecting them to rigorous testing and statistical validation, allowing us to identify when a signal is truly valuable and when it’s just noise.

However, there are significant challenges to advancing the study of TA in this way.

1. Reluctance of traders to share their methods: Many successful traders are secretive about their techniques. If a trader discovers a particular pattern or indicator that reliably generates profit, there’s a strong incentive to keep that edge to themselves. Without transparency, it becomes difficult for the broader financial community to analyze, test, and validate these methods scientifically.
2. The subjectivity of TA: Some TA seems to work for some traders, but most TA doesn’t seem to work for most traders. It seems likely that a lot of effectiveness comes from implicit learning where traders use TA as a simplifying model rather than a direct trading signal.
3. The evolving nature of TA: Unlike folk medicine, which is based on static traditions passed down through generations, TA is constantly evolving. New indicators are developed, and old ones fall out of favor. This fluidity makes it harder to study in a systematic way. What works in one market condition may not work in another, or a new generation of traders might change the way a particular pattern manifests itself, rendering older studies obsolete.

Despite these challenges, the analogy to ethnopharmacology offers a constructive framework. By accepting that some elements of TA likely do work, we can begin to study why they work. This approach would lead to a better understanding of the psychological and behavioral drivers of market movements and could help create a more evidence-based framework for TA. In the end, much like folk medicine, TA likely contains valuable insights that are not fully understood or appreciated today.

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