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Rating: 
Summary: Not worthy to present itself as a serious work
Review: I expect that I am not the only reader to conclude that Christopher May has only a cursory grasp of nonlinearity. As a reader of philosophy and religion and a mathematician with research experience in nonlinear dynamics, I kept wondering when the "hand waving" and "name dropping" were going to yield to some cold, hard analysis or practical application. I might even have settled on a few unproved practical pricing applications!To add insult to injury, this book was poorly edited: papers were discussed as if well-known, then introduced five paragraphs later; whole paragraphs were repeated several times, as if the book had been a series of independent pamphlets stapled together; anecdotal musings ran on for pages with no purpose apparent other than to impress the reader with the author's erudition; typographical errors peppered the few mathematical expressions. I have similar complaints with Edgar Peters' books, but at least Peters understands nonlinearity sufficiently to have applied some famous techniques to problems in financial valuation. One can hardly escape the suspicion that Christopher May is a long-winded "poseur."
Rating:
Summary: Ego trip with virtually no useful baggage
Review: If you're looking for a good primer in fractal economics, do not waste your money, or worse, time with this book. You can get more information and less noise from E. Peters's "Chaos and Order in the Capital Markets". The most useful information you'll get from this book is a description of the Hurst exponent; the rest is, well... I don't mind random musings with an articulate friend after dinner, but please don't do it in a pedagogical-sounding, inflated tome. Let the quotes describe themselves: "... this chapter will present a challenge because it exists at a rarified level of understanding." "I maintain, as any good scientist does, that the theory must fit the facts". "The mathematics in this chapter may be complex to the financial economics professional" (I found the series summation as the most complex math in that chapter.) Errors and carelessness are so prevalent, this book really brings down my opinion of the JW editors. Concepts of dependent and independent variables are mixed up, atrocious-looking graphs of normal and Levy distributions are shown, notations like "m2" are printed instead of "m(superscript)2" to mean m-squared, etc. Most of the time is spent waxing philosophical connections among shallowly described concepts like Fourier transform, superstrings, the scriptures, Brownian motion, Socratic logic, etc. To be fair, if this sort of shooting-the-breeze provides a relaxing read for you, this book might fit the bill. The author breathlessly describes "original concepts" like fixing risk for varying returns in security portfolios: this is already done with instruments like mortgage securities. Perhaps the author's own quotation of Occam's Razor should have been heeded, "That which is not needed should not be included". I did find the Bloomberg KAOS screen description on page 128 useful. If you use Bloomberg, you can also get that from the manuals.
Rating:
Summary: Ego trip with virtually no useful baggage
Review: If you're looking for a good primer in fractal economics, do not waste your money, or worse, time with this book. You can get more information and less noise from E. Peters's "Chaos and Order in the Capital Markets". The most useful information you'll get from this book is a description of the Hurst exponent; the rest is, well... I don't mind random musings with an articulate friend after dinner, but please don't do it in a pedagogical-sounding, inflated tome. Let the quotes describe themselves: "... this chapter will present a challenge because it exists at a rarified level of understanding." "I maintain, as any good scientist does, that the theory must fit the facts". "The mathematics in this chapter may be complex to the financial economics professional" (I found the series summation as the most complex math in that chapter.) Errors and carelessness are so prevalent, this book really brings down my opinion of the JW editors. Concepts of dependent and independent variables are mixed up, atrocious-looking graphs of normal and Levy distributions are shown, notations like "m2" are printed instead of "m(superscript)2" to mean m-squared, etc. Most of the time is spent waxing philosophical connections among shallowly described concepts like Fourier transform, superstrings, the scriptures, Brownian motion, Socratic logic, etc. To be fair, if this sort of shooting-the-breeze provides a relaxing read for you, this book might fit the bill. The author breathlessly describes "original concepts" like fixing risk for varying returns in security portfolios: this is already done with instruments like mortgage securities. Perhaps the author's own quotation of Occam's Razor should have been heeded, "That which is not needed should not be included". I did find the Bloomberg KAOS screen description on page 128 useful. If you use Bloomberg, you can also get that from the manuals.
Rating:
Summary: Completely Useless
Review: Optimistically I bought this book expecting an insight into non-linear models of price behvaiour, maybe some thoughts I could use to flesh out my own experience - a peek into other approaches to managing price volatility perhaps. What I got was a rehash of technical analysis with a glaze of chaos theory. Don't bother.
Rating: 
Summary: How not to title a book.
Review: Someday in the not too distant future, nonlinearity will be an unquestioned first principle in the metaphysics of nature, man, mind, and the markets. And Christopher May's Nonlinear Pricing will simply be one of many books heralding the coming of this new view of reality. Count among them The Metaphysical Foundations of Modern Physical Science, E.A. Burtt (1924); Holism and Evolution, Jan Smuts (1926); New Metaphysical Foundations of Science, Willis Harman (1994); The Evolving Self, Mihaly Csikszentmihalyi (1993); The Web of Life, Fritjof Capra (1997); any of the work on desertification and range management by Alan Savory and on medicine and prayer by Larry Dossey, M.D. The list goes on and on, including the many works cited in May's book. Why so many titles over so many years by so many authors in so many different fields? Why so little general knowledge of nonlinearity? Why so many ruffled feathers among the reviewers of May's book? (The true believers question his understanding of the component parts of nonlinearity. The nonbelievers question his sanity, writing him straight - as in linear - off. The solution seekers want to know where's the beef, the silver bullet, the keys to the kingdom, and are mighty mad when no answer is forthcoming.) Go back and read Thomas Kuhn's The Structure of Scientific Revolution (1962) for answers to the questions and a complete justification for the importance of May's book. Paradigm shifts - the insight that made Kuhn famous - are nonlinear, providing one more case of anecdotal evidence for the validity of May's thesis. Kuhn started as a physicist and became a historian of science when he noticed that the real story of scientific discovery is hardly additive (that linear word again). Rather, science is a random piecing together of a bit of information here, another bit there, until - like the self-organizing button and thread web described in Stuart Kauffman's At Home in the Universe (1995) - a nonlinearly ordered system emerges from randomness. I expect Kuhn would have called a paradigm shift "emergent order" characteristic of everyday nonlinearity had he had the vocabulary. But he didn't. Instead, Kuhn invented his own terms - just as May notes George Soros had to in his equivalently nonlinear description of the markets in The Alchemy of Finance (1987). For Kuhn the terms of science are black and white. Post-paradigm shift, science is merely a matter of filling in the pieces of the newly organized nonlinear puzzle. Pre-paradigm shift, science is a mishmash of publications hinting at the same subject whose authors seem to spend more time on backbiting than research. Sound familiar? Christopher May is to be applauded for nudging along the metaphysical paradigm shift from linearity to nonlinearity. He greatly expands the scope of the nonlinear connections through his extensive citations and explication. What he has to say is hardly the last word on the subject and may be a difficult read for many, but it is worth the effort. I run a fund management company and a venture capital fund based on the tenets of nonlinearity and I welcome every author who helps advance the cause. I make this comment not to be self-serving but to be of service. The world is not flat nor is it round. It is nonlinear
Rating:
Summary: Contains no substance or even one concrete idea
Review: The book can be summarized in 11 words: "Genetic fractal neural fuzzy chaotic nonlinear stuff good. Traditional finance bad." There is no real information in the book. There are unsupported anecdotes and a myriad of quotes from non-financial sources. The lack of substance in the text leads one to suspect that the author himself doesn't understand the underlying mathematics himself. For a better source, Chapter 12 of Econometrics of Financial Markets by Campbell, Lo and MacKinlay has more information on nonlinear modelling than the whole of this book (and it has a couple hundred pages on traditional financial economics.)
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