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When market technicians who have been trained in the scientific method and empirical standards of scientific research look at the stock market, they are typically in search of a special type of truth, scientific truth.
Scientific truth comes from the positivist tradition which says that truth exists independent of the human mind and human s senses.  This rules out our ability to both perceive and shape that truth. As such, scientifically trained technical analysts look for techniques that add value in the same way they search for certainty in the laws of physics.
They are trying to find indicators, techniques, processes that are true and work in all markets and at all times. This is such a high standard of evidence that the valid echnical analysis they have found offers such slight advantages that there is practically no edge.
Scientific technical analysts generally considered there to be four different categories of technical analysis:
1. Subjective: these are technical analytical insights which cannot be quantified, defined w or tested. To a scientist, these would deserve no consideration because there's no way to objectively determine the truth value of their content.
2. Objective methods of unknown value: these are quantifiable techniques and indicators but which have not yet been subjected to rigorous scrutiny in multiple market conditions with properly constructed data sets and independent verification. These are interesting topics for research but once again have no truth value.
3. Objective methods that add no value: this is where the scientists have spent most of their time, because t there are an extraordinary number of indicators and techniques that cannot pass the statistical standard of being robust in all market conditions. Scientists proceed towards the truth by ruling out those things which are false, in the tradition of Sir Karl Popper and his doctrine of falsifiability.
4. Objective methods that add value: if you processes and indicators that have achieved the status must pass two tests. The first test is that a statistical significance. The second test is that of economic significance. There are actually some indicators and techniques that are statistically significant edges but which cannot be realized in economic terms because the cost of implementation outweighs the value add in the real world.
A mixed methods trader, who is not bound by the scientific rigor of the positivist tradition is s satisfied to find heuristics and rules of thumb which offer probability distributions better than random and are content to trade their edges where they find them. It is clear however that the scientists have added a great deal of value to the literature of trading by pointing out how many things are just not true. For this we owe them a great deal of gratitude.
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