The Bibliography alone is worth the price of admission

books:


	• Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals David R Aronson Wiley, 2006 - 544 pages average customer review:based on 41 reviews view larger image
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highly recommended

The Bibliography alone is worth the price of admission

My experience with "technical" trading books has been that they are
either pseudo science of the quasi-astrological variety (eg, wave
theory or fibonacci hocus-pocus) or entertaining and vague
reminiscences of some successful trader(s). The "serious" literature,
instead, is written in statistical/mathematical formalisms which you
may be able to understand given an adequate background, but even then
serious effort and time is required and the sheer distance from the
formalisms to the pits is fraught.

Professor Aronson has done an admirable and unique job of dispensing
with the hocus-pocus and applying the requisite rigor to the many
difficulties associated with analyzing the results of historical
backtesting and datamining. His bibliography seemingly covers all
serious (and some not so) references of interest to the algorithmic
trader. Months after having consumed the book, I still refer to the
bibliography to glean interesting sources.

As an earlier reviewer noted, the early portion of the book in which
he debunks TA and establishes basic statistical literacy for later
chapters may or may not be of interest to many readers, but his
chapters five and six are genuine contributions to the field and
should be read, studied and implemented by anyone looking to derive
tradable strategies based on historical testing.

Anyone who has spent time attempting to optimize parameters or
otherwise evince trading rules from historical data will have quickly
learned that if you look at enough cases, you will always find
something that looks good but (alas!) really isn't. Fool's gold,
indeed! This is the first trading book which directly addresses this
issue in a rigorous yet accessible fashion.

This is not the book for someone who is looking for the magical key to
a kingdom of riches (I recommend Voltaire's "Candide"). But if you
are an algorithmic trader looking to get a statistical grounding and
some concrete methods for assessing your backtested results, there's
simply no better book available.

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A wake up call.

Evidenc based TA is a wake up call, to all practioner of technical
analysis. This book is refreshing in the fact that David Aronson a
long time practioner of TA, gets to the core of the matter by
implementing a method of quantifying TA via a valid back testing
method. A real eye opener for those who use TA, who need to really
test there methods, and the formulas in this book will give a guide
line on how to do just that.

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Excellent book about mechanical trading and testing

Even though Aronson does a fine job of convincing the reader of just how difficult it is to design consistently profitable mechanical trading systems, there is plenty in Evidence Based Technical Analysis to interest the committed system designer. The book is particularly strong in the following areas.

- It is an excellent manual on how to test trading strategies thoroughly.
- The discussion of "technical analysis theory" in relation to economic theory is first rate.
- The dangers of data mining and data snooping are spelt out in no uncertain terms. Many will change the way they approach their testing and interpretation of findings as a result of reading this book.
- Even though the book spells out just how difficult it is to develop consistently profitable trading systems, system developers are likely to find many new ideas for future testing.

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Must read for TA traders

I like the book, answered some of the TA questions that I had. The part that involve statistic should have been written by someone with more knowledge on resampling.

The book could have been 1/3 its size (this 1/3 alone worth the 4 stars I gave this book). Readers should also consider books on basic statistic and resampling to strenghten the theory behind the concept.

reviews: 1, 2, 3, 4, 5, page 6, 7, 8, 9

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