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Why Technical Analysis is Controversial (and How to Use it Properly)

Technical Analysis is one of those topics that divides a lot of people in the #trading community--some people love it, and some people hate it.


In this article, we show why #TechnicalAnalysis is so controversial, and what is the most productive way to understand technical analysis, and how to use it properly.


**This article is adapted from a series of lectures from my Coffee Trader's Course.**


Why Its Controversial

One of the biggest complaints against technical analysis is the lack of scientific evidence, but we will see that there is plenty of scientific evidence available, but also how this is not straightforward.


The controversy of technical analysis begins with the name. The name “technical analysis” implies that this is some kind of science with hard and fast rules and correct answers.


So what is technical analysis, and what is the evidence for it?


Technical analysis is a discipline that looks entirely at price action itself (and to a lesser extent, other trading data like volume and volatility), for signals on how to trade profitably.


The core thesis of technical analysis is that prices tend to move in “trends” that continue in one direction for a period of time. Therefore, the goal is to identify when a trend has started or is about to start.


Modern Technical Analysis can mostly fall into 1 of 3 categories:

1) Chart Patterns

2) Moving Averages

3) Technical Studies


We will elaborate on these in subsequent articles, however, I want to highlight that looking at price action to predict the direction of price is an old idea that predates modern charting software.


Famed, early 20th century stock trader Jesse Livermore had a system for “reading the tape” (a printed paper-tape of stock prices), Ralph Nelson Elliot invented Elliot Wave in the 1940s, and Charles Dow developed Dow Theory in the late 19th century and early 20th century.


Japanese Candlestick charts are purportedly much older, and my own research into 18th century rice futures trader, Honma Munehisa has confirmed his observations on trends.


However, the fact that a discipline is old does not mean that it is scientifically valid. Astrology and Tarot Card reading are thousands of years old and persisted into the present but have been shown conclusively to be ineffective in predicting the future.


The criticisms against technical analysis are several but here are some of the strongest:

1) Self-defeating prophecy: the more successful a system is, the more its value will decline. Volume tends to increase slippage, so if everyone trades a signal at the same time the value will diminish for the participants.

2) Ambiguity of chart patterns: Chart patterns often lack clear, objective rules for what a chart pattern purports to show. Is this a “rounded bottom” reversal or a “cup and saucer” continuation pattern?

3) Lack of convincing theoretical explanations: How does a “cup and saucer” pattern in prices show that a trend is going to continue?


On top of all of these, there is the problem of evidence. Here is a recent informal study from a few years ago that found significant negative correlations with technical indicators. In other words, using technical analysis had statistically significant record of losing money (the exception? Bitcoin of course).



One of the biggest problems with Technical Analysis is that you can only test it in the past.


Wait, isn’t all available data, past data? Yes, but the problem with a trading system is that it influences the market.


This is the fundamental problem of backtesting.


Backtesting is when you come up with a trading system, and then use historical price data to see how well your strategy would have worked. Backtesting is a great tool to evaluate systems but it is limited by the fact that it cannot account for the impact of your strategy itself on the market.



Every time you buy #stocks, or #futures in a liquid market, you raise the price of that security. This impact is magnified the faster you put on your trade, and the more volume that you put on.


For example, if you buy 1,000 lots of coffee futures all at once you will have a massive impact on price: you might raise prices by 10-20c...maybe more if it was a less liquid market or time of day.


If the price of coffee spikes from your massive buy, that will influence other traders in the market who will maybe take this as a signal that prices are overvalued and will sell, or perhaps take it as a signal that the trend is bullish and buy. We don’t know how they will react.


However, we do know that this can set off a chain reaction that will influence how prices unfold.


Contrast this with testing a weather forecast model.


If we test a weather prediction system that evaluates past weather patterns and predicts weather in the future, we can evaluate those systems in the present, to see how well they compare to our models.


The fact that we are predicting higher or lower temperatures, faster or slower winds, or the quantity of rainfall, does not influence those systems themselves in any material way. Therefore, we can assume that the conclusions are much more robust than we could glean from backtesting financial strategies.


Evidence in Favor of Technical Analysis

That said, there is a decent amount of academic literature supporting the idea that technical analysis and technical trading systems do work.


One of the first academic papers that I came across that studied technical analysis was a 2003 paper, “How rewarding is technical analysis? Evidence from Singapore stock market” by Wong, Manzur and Chew. This paper studied several quantifiable technical analysis strategies and concluded that they would have been profitable (although they suffer the above problem of #backtesting).



There are other more recent papers, such as “Technical Analysis and Discrete False Discovery Rate: Evidence from MSCI Indices” by Sermpinis, Hassanniakalager, Stasinakis and Psaradellis, published in 2019.


There is also plentiful anecdotal evidence from successful traders like Paul Tudor Jones, and the Trend-Following “Turtle” traders who learned a trading system and then went on to become successful #hedgefund managers.


In my own experience trading prop, my most profitable strategies were simple moving average #tradingsystems in the #coffeemarkets.


So if it is at least theoretically possible that Technical Analysis can work, then how should we think about it, and how can we trade it profitably?





The Proper Framework

My observation on technical analysis is that it is really a subset of #CrowdPsychology, and that Tech Analysis can be both understood and successfully traded upon.


Crowd Psychology is a subset of social psychology that traces its origins to the late 19th century, and is intimately connected to financial markets. Two books are pivotal here: “Extraordinary Popular Delusions and the Madness of Crowds” by Charles Mackay (published 1841) and “The Crowd” by Gustave Le Bon (published 1895).



These two books both recount various instances of manias and delusions shared by multitudes of people concurrently. These include obsessions with witchcraft, pseudo-sciences like alchemy and astrology, as well as more general crowd behavior such as rioting. Notably, some of the most prominent of these crowd behaviors are manifested in #financialbubbles.


A financial #bubble is generally considered to be irrational, but I would contend that it is not so much irrational as it is emotional contagion. My observation in the #coffee #markets is that coffee often follows the pattern of a financial bubble, but that doesn’t necessarily mean that there was no fundamental reason for this to occur. It just means that whatever the reason, many people adopted the views of those around them.


Financial bubbles also have a repeatable format and characteristics. Two prominent pioneers of Technical Analysis, Charles Dow and Ralph Nelson Elliot, emerged in the late 19th century/early 20th century and they were some of the first to describe characteristics of trends in the financial markets.



Dow was a financial journalist who developed “Dow Theory” over a series of articles in a little, hometown newspaper he founded, “The Wall St Journal”. In these articles he outlined the 6 tenets of Dow Theory that he observed in trends.


Ralph Elliot noticed that markets seemed to move in fractal, wave-like patterns. His method of describing price action and its use in predicting prices became known as Elliot Wave Theory.


The similarity between financial bubbles, Elliot wave and Dow theory trends all stem from the fact that they are describing crowd behavior driven by emotional response to prices.



How to Use it Properly


My view on using technical analysis to trade relies on two key factors.


First, technical analysis is based on attempting to extrapolate market sentiment (emotion of the crowd) from price action.


Second, technical analysis patterns and indicators should only be used if there is a logical understanding of what they are supposed to indicate.


Both of these considerations are really an attempt to combat what I consider to be the biggest “misuse” of technical analysis: ignorant belief.


Ignorant belief is something akin to what is required of a practitioner of Tarot Cards or Astrology. The practitioner may be a sophisticated understanding of how the system works, and what it is supposed to achieve, but there is no logical explanation for why it should work.


My advice for aspiring technical analysts is simple: if you don’t understand why the chart pattern or technical system should work, don’t use it.


Using tools that you don’t understand is a dangerous practice in general, and that goes doubly true for trading.



The framework that I use to understand technical analysis, is psychology. I adopted this framework from famed trader Alexander Elder. Elder was a clinical psychologist who escaped the Soviet Union and ended up trading financial markets in the United States.


In his book, “Trading for a Living”, Elder outlines his philosophy for trading that makes heavy use of technical analysis indicators and systems. What I really liked about this book is that for every indicator that he recommends, Elder outlines his interpretation of the psychology that the indicator represents.


Now I should clarify, when I say that I use "psychology" as a framework to understand technical analysis, specifically, I mean that I'm looking for shifts in crowd sentiment. In other words, I’m looking for signals that the crowd is adopting a consensus or that the consensus is shifting.


As a simple example, a head and shoulders reversal pattern indicates that the crowd has shifted its sentiment from one direction to another. The bearish version of this pattern is characterized by an uptrend that pulls back (left shoulder) and then makes a new high and pulls back (the head), followed by a rally attempt that fails to make a new high and pulls back to a new low (the right shoulder). To me this indicates that bullish sentiment (crowd optimism) has peaked and is now trending lower (crowd pessimism).



We can see that bullish optimism was high in the crowd because the market made new highs (the head), but that this sentiment has changed because now, not only are we not making new highs (right shoulder) but we are making new lows. In order for this to happen would mean that more traders are becoming bearish out of the group which translates into a shift in sentiment.


If our theory of contagious emotions holds true, than we can expect that this bearish shift in sentiment will catch on and attract more bearish sentiment.


Another example would be a #BollingerBand in a sideways market. The Bollinger Band is constructed by taking a 20 day standard deviation of prices and applying that number above and below a 20 day simple moving average.



In this case, the SMA represents consensus on price, and the std dev represents extremes compared to the consensus. This is typically traded by “fading the range”, where the top of the band is sold and the bottom of the band is bought. The #psychology behind the strategy is that crowd has consensus on what value is in this market and that prices will revert to this value.


Neither of these strategies are infallible by any stretch. Sentiments can and do change all of the time for a variety of reasons, but by having an understanding of what you are trying to capture with these two strategies will help you to understand when it is a good time to employ them, and when they may not be relevant.


Conclusion

It is not my intention to convince you that you should or should not use technical analysis in your own trading strategies, instead I want to offer a framework for how to think about it. There have been many successful traders who use technical analysis and it’s a valid strategy, but there are also many examples of traders who were unsuccessful using technicals as well (they just aren’t as famous).


In my own experience as a trader, and more importantly, in my studies of successful traders, I have learned that there is a magic bullet to trading. However, its not technical analysis, its not fundamental analysis either. Instead, its understanding what you are doing, why you are doing it, and when the situation has changed.


This article is adapted from a series of lectures from my Coffee Trader's Course.

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