Book review: Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals, by David Aronson.
This is by far the best book I’ve seen that is written for professional stock market traders. That says more about the wishful thinking that went into other books that attempt to analyze trading rules than it does about this author’s brilliance. There are probably books about general data mining that would provide more rigorous descriptions of the relevant ideas, but they would require more effort to find the ideas that matter most to traders.
There hasn’t been much demand for rigorous analysis of trading systems because people who understand how hard it is to do it well typically pick a different career, leaving the field populated with people who overestimate their ability to develop trading systems. That means many traders won’t like the message this book sends because it doesn’t come close to fitting their preconceptions about how to make money. It is mostly devoted to explaining how to avoid popular and tempting mistakes.
Although the book only talks specifically about technical analysis, the ideas in it can be applied with little change to a wide variety of financial and political forecasting problems.
He is occasionally careless. For example: “All other things being equal, a TA rule that is successful 52 percent of the time is less valuable than one that works 70 percent of the time.” There might be a way of interpreting this that is true, but it’s easy for people to mistake this for a useful metric, when it has little correlation with good returns on investment. It’s quite common for a system’s returns to be dominated by a few large gains or losses rather than the frequency of success.
The book manages to spell Occam three different ways!