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Review: Evidence-Based Technical Analysis by David Aronson

April 4, 2014 by Andriy Moraru

Evidence-Based Technical Analysis by David AronsonThere is one book I now deeply regret not reading near the start of my way as a Forex trader. Although I have started back in 2005, late 2006 when Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals had been first published, was still what I would call a dawn of my career. The funniest fact is that the book barely mentions Forex at all.

It was written by David Aronson, a professor of finance in the Zicklin School of Business at the time of writing the book. He did not publish any other significant books since release of EBTA. He also manages a website called Evidence Based Technical Analysis (not updated since 2009). Currently he is a president of Hood River Research company.

The main point of the book is the supremacy of what the author calls objective technical analysis over subjective technical analysis. It is discussed and proven in the first part of the book. The second part is dedicated to a case study of testing the objective TA rules using objective TA criteria.


The following ideas are expressed in Evidence-Based Technical Analysis:

  • Subjective TA rules cannot be properly tested, and their efficiency cannot be measured.
  • Objective TA rules can be tested and researched using scientific methods.
  • Human history proves that scientific methods brings superior results compared to other methods.
  • A set of psychological biases is working against traders when they fail to implement rigorous objective methods in their rule development and execution.
  • Despite the markets being probabilistic in their nature, it is possible to scientifically test various trading rules and make correct conclusions regarding their efficiency.
  • Statistical analysis and confidence intervals should be used to explore and describe viability of TA rules.
  • Data mining (backtesting) is probably the best tool in the hands of an objective TA practitioner.
  • Even though data mining is prone to data mining bias, it can be accounted for using certain statistical methods.
  • The role of a technical analyst is not to produce the end-product (analysis, signals), but to create ideas, which are to be tested and executed by automated systems. Otherwise, analysts will always be prone to falling back to the inferior subjective TA methods.

Research Results

Apart from a purely speculative and educational part of the book, there is a complete case study of testing more than six thousand trading strategies on S&P500 index futures. The case study is basically a backtest of so many rules on a multi-year period of S&P500 chart data plus some additional data sources (other market data, interest rates, volumes, etc.)

Because the case study aims to select the best trading strategy of several thousands, it is clearly a data mining endeavor and thus prone to data mining bias. The author uses improved White’s Reality Check and Monte-Carlo permutation methods to mitigate the effects of the data mining on the obtained performance results. The aim of the whole backtest is to find out whether any of the tested rules offer returns better than zero (or those obtained using random entry/exit signals) with a statistical significance level of 0.05.

I do not think that I will spoil the book much by telling you that no such strategies were found among the tested ones. There were profitable backtest results (the best rule with more than 10% annualized return), but in all cases, such result was due to data mining bias and had no statistical significance (p-value > 0.8).

That does not mean that the experiment was useless or that there is no point in reading about it. On the contrary — it is probably the most enlightening and inspirational experience you will probably have if you have never practiced true objective TA before.


If the pros of the Evidence-Based Technical Analysis are not obvious to you after reading the review till this point, here I present a condensed list of advantages:

  • The biggest advantage is the introduction of objective TA concept. Of course, I cannot say that no one except David Aronson does that, but for me, personally, it was this book that opened my eyes on this important topic.
  • A very gradual approach to introduction of the scientific methods into trading. It is a very complex subject — it involves a lot of theory and explanations. David Aronson does a great job laying it all out withing boring the readers and without omitting anything important that could be crucial to understanding some of the aspects of the objective TA.
  • A lot of ideas for your own TA rule development and organization of the testing process.
  • Countless references to other works in the field, which allows readers not only fact check the book’s statements, but also to deepen one’s knowledge in the area.
  • Not a humorless style of writing, which makes the book significantly easier to read.


There is not much to talk about regarding the disadvantages of this book, but I have to mention some:

  • Typos and errors. While there is nothing significant about the former, the latter is getting too far in this book (at least its Kindle version). Some of the paragraphs are swapped places, whole words are omitted, and that is in addition to a rather high complexity of the covered subject.
  • It is too focused on S&P500 as the market for testing and stocks in general as the model of the market. Although it can even be an advantage if you are more of an equity trader, but for the currency traders, it is definitely a downside.
  • The book was written in 2005–2006, so a lot has probably changed in the field and, unfortunately, you would need to find out about those changes from other sources. A newer edition of the Evidence-Based Technical Analysis would definitely help here.
  • The author fails to mention that it is very difficult to divide whole trading into two realms of objective and subjective rules. For example, it is not possible to backtest insider trading, but it definitely should have some edge.

Why read it?

The main reason to get this book and spend some 15–20 hours reading it is that it will probably change your whole concept of FX strategy creation, formulation, backtesting and implementation. It will be most useful to those who develop their own strategies or create expert advisors for sale. On the other hand, common traders, who buy systems or subscribe to signals, will also find a lot of useful information. It will help them revise their preferences and spend time and money more wisely.

There are two categories of traders that probably will not benefit from reading Evidence-Based Technical Analysis at all. The first one is composed of traders who already practice purely objective trading. The second one is the traders who practice subjective methods of trading but experience a long-lasting and tremendous success with them. Perhaps, they have found their holy grail; reading this book will just distract them.

If you have any opinion, questions or comments about Evidence-Based Technical Analysis by David Aronson, please feel free to submit them using the commentary form below.

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