Most financial market books, especially those on TA, seem as though addressed to prospective targets: “Suckers, use my superdooper-specialized proprietary method, trade a lot, get my newsletter, and open an account at my very own, highly recommended XYZ brokerage firm.” They are, generally, composed of descriptions of too-well known indicators, replete with glowing, yet unsubstantiated, accounts of the profits the author has obtained by using them. Even the more serious attempts, like those of John Murphy, are merely encyclopedic gatherings of indicators, with little effort made to determine their objective utility or profitability; or, like Kaufman’s, while addressing a more intelligent, educated technician, too compendious. Sadly, the better books present the reader with barely more than introductions to approaches that are mathematically and computationally more rigorous; and, while they may also indicate further directions of study, do little in the way of providing it.
This book, I am happy to say, avoids all of these objections.
The author discusses and describes a number of statistical methods, and develops them into tools with which to measure and identify market development and direction. And though his instruction is often brief, it is to the point. This adds a certain density to the presentation, but it IS presented. As an example, he uses a quantile segregation of price-data to reduce the adverse effects of noise in a moving average. He indicates in two sentences the formula to use in EXCEL to obtain it. Testing of these tools is, of course, the responsibility of the reader, but there is no arguing the fresh, original character of these methods, and the patience with which the author explains them. If nothing else, it stimulates the imagination. Wait, that is everything, isn’t it?
Very highly recommended.