“Quants are not gonna make it. They carry too much baggage. Technicians are going to be the ones to make the next big opportunities“. In Twitter, this statement was attributed to John Bollinger and made in the last CMT conference. I was not there but I am here to try to understand what it means.
The above statement assumes that being a technician is different from being a quant and vice versa otherwise it is meaningless.
However, at the CMT Association website, the following are listed as part of the knowledge domain:
- “A scientific method for market analysis and analyzing price & volume data”
- “Recognizing market-based signals that define probabilities and opportunities for exploiting both continuing trends and mean-reverting behavior”
- “CMT candidates learn how to develop a repeatable process for making decisions”
The above sound similar to what quants do.
So, why is a market technician different from a quant according to John Bollinger?
One possibility is that the market technician body of knowledge has changed over the years to include a more quant-based approach but many still think of a technician as a chartist. There are many chartists in social media for example. I am sure they consider themselves market technicians but quants do not do this type of thing.
How scientific is drawing a trendline in a chart, or identifying some pattern, such as a head and shoulders, while assuming that this provides any useful information about future price action? Obviously, anyone who understands the scientific method will tell you this has little to do with science but it is an empirical approach and apparently a few people can be good at it. But it is difficult to differentiate between luck and skill from the group of successful chartists, in other words, from success of individuals we cannot infer a successful method.
It appears to me that a market technician for most people is not a quant but someone who uses the charting method. This is in agreement with John Bollinger’s statement. At the same time, it also appears that CMT Association wants to distant themselves from charting and are adopting a more modern and systematic approach. This is good but there is a problem.
The problem is that quant is heavy in math and many that get involved with the markets, such as those who draw lines and look at a few indicators, are usually not good at math. Actually, the “baggage” referred to by John Bollinger may be the math and the quants who are not good at it “are not gonna make it.”
When viewed from this angle, I fully agree with John Bollinger’s statement but again he may not have meant this. But he has been around long enough to know that most people are not good in applying quantitative methods to the markets although they can be very good at drawing lines on charts.
At the same time, quantitative methods face several challenges: small samples, data mining bias, non-stationarity, complexity, etc. Some of these problems are also present in simple charting analysis. For example, when a chartist reviews 500 charts during the weekend and finds one or two that meet certain criteria, this is data mining essentially: selecting a few charts that pass the criteria ignores a large number of charts that did not. The results can be due to confirmation bias.
All I can say without making this difficult to read is that being successful is hard for both technicians and quants but a quantitative approach is more compatible with the scientific method. As a result of this and the rapid adoption of quant methods in investments world, it appears that the CMT Association is shifting towards that direction. But the broad adoption of quant is not going to make it less effective if that was what John Bollinger alluded to. The reason is that quant methods cannot be popularized on the scale similar to that of classical technical analysis. Technical analysis and specifically charting became popular because they were easy to teach and learn and provided the dumb money professional such as CTAs needed to realize huge returns in the 1980s and 1990s.
Quant is unlikely to provide dumb money on the same scale as charting methods due to risk and money management. The idea that some market technicians will be better positioned in a quant world is a good one provided that the problems mentioned above that plague their method can be dealt with. This is unlikely and a few survivors will not probably be enough to declare a win against quant. It is also highly unlikely that serial correlation will ever return to the markets to make some of the old technical methods profitable again as in the 1980s and 1990s. For more details see my interview for Forbes.
My conclusion is that CMT association appears to be updating the curriculum to make it more quantitative and this is a good move but still some experienced professionals, an example is John Bollinger, draw a line between quant and technician and this probably makes sense also from the perspective that many technicians will never be able to transition to quant mode due to the requirements involved.
More details about some of the perils of technical and quant analysis can be found in my book Fooled by Technical Analysis: The perils of charting, backtesting and data-mining.
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