First, he notes the following typo:
An example of the sloppiness (and there are many) is on page 21, "The key to the portfolio approach is the variance of two random variables is less than the sum of their variance." This makes no sense. He might mean "The variance of THE SUM of two random variables is less than the sum of their variances,"
Alas, he is exactly right. I meant 'variance of the sum' but wrote 'sum of the variances'. A classic brain fart, like writing 'the wet was water', a phrase one's brain turns into 'the water was wet' when you read it 50 times because that's what brains do, and reading it over and over makes it even harder to see.
Fundamentally, there was only light editing of my work. I recognize that meticulousness is not one of my strong points, and should have paid for extra editing, but I was grateful to Wiley for publishing my book, and so took what I got. As the list of acknowledgements will attests (ie, none), this book did not benefit from extensive vetting. There are about 5 such mistakes, and as to whether this is 'many' is a matter of perspective. Yet in context generally it was obvious as to what is meant. For example, in this case it was right above a graph that shows that portfolio variance declines as a function of portfolio size, and talk about how diversification lowers risk. But I can sympathize that such mistakes are distracting.
Brown also bemoans the $95 price. Gee, I didn't know anyone would pay that much. Amazon sells it for about $60, and the 'used' copies are basically new copies released to small stores that are selling it, and these go down to $52. Nevertheless, it is above the usual $20 to $30 one is used to paying for books, but it's a niche, and books with math usually have sufficiently small audiences that such is the price. I would have liked to sell a $30 book so it could be at Barnes and Noble, but it's a rather specific, technical arguement with a limited audience.
A final criticism was that I "Lack of appreciation for other people's thought", and he specifically mentions Taleb. Alas, I have Taleb fatigue and consider him a lightweight blowhard, not The Establishment I am criticizing (represented by, say, Fama, French, Cochrane, Campbell, Harvey, Schwert, etc.). In a sense, like Taleb, I am criticizing the Establishment, but we have as much in common as typical third party candidates. Considering that Taleb's main empirical points are about fat tails and peso problems, these are standard problems and are addressed through the extant, large literature, that exists independent of Taleb.
But in general, I think I amply provide references to earlier research, and for almost every empirical point provide specific papers. My novelty, empirically, is highlighting that the scope of data suggest a flat risk-return relation in general; each individual finding, such as within equities, or currencies, points to literature in that domain, literature that is often quite deep.
The book's summary of quantitative finance is backed up by lots of references, but I would bet that the author has not read all the references. He doesn't even seem to be familiar with Hyman Minksky's work, and he was a graduate assistant for Minsky.
Actually, I have thoroughly read all my references, and I do appreciate Minsky's work (I was his TA as an undergrad, not grad), and noted the Minskian notion of Keynesian uncertainty was not fruitful because metrics of uncertainty, emprically, are not positively related to returns (eg, IPOs, or firms with relatively high amounts of analyst forecast dispersion, have lower returns than average).
Brown then states
And "expected return" only makes sense in a rigorous context (who does the "expecting," and when?). The author scorns rigor, but then uses the concept of expected return in a model with divergent expectations among investors, without discussion of whose beliefs define the expected return, and fails to distinguish that concept clearly from ex post average return and market-clearing return.
I don't make a distinction between long and short term expectations, and most asset pricing models are simple one-period models. In many cases, one can find short and long term expectations have different properties unless returns have certain distributions, or utility functions have specific functional forms, and generally these discussions lead to hair splitting, and generally add little insight. Thus, like almost everyone in this space I found this distinction an uninteresting complication. More fundamentally, expected returns should equal average returns over large enough sample, just as a sample mean converges to the population mean over time. That so many assets show sample means in direct contrast to theory implies to many of Finance's founding fathers that 'expected returns' are hard to measure, but after 50 years I find this rather uncompelling.
But let's get on to the good things he had to say, after all, it was 3 stars, not 1!
What I like about this book:
* It contains important new ideas that can help any risk-taker with quantitative skills succeed
* It challenges conventional wisdom
* The meat of the book is based on practical experience, not just things that seem right to the author, but things he has tried, and generally with success
Those are good things, I think, and highlight in make a new point about something important, with a practical slant. I think for $52, even with typos, that makes it a good buy.
Brown ends with
This idea is integrated into a reasonably complete financial theory. The foundation seems solid but, as described above, its superstructure is jumbled and ugly.
The ugliness? I too dislike ugliness. I did not want the book to be too technical, however, so my fundamental model is a bit incomplete in the book, but the gist is rather simple:
As shown in the table above, Y is usually considered riskier, with a 60 point range in payoffs versus a 20 point range for X. Yet on a relative basis, each asset generates identical risk. Everything follows from that. The proof of this is rather straightforward, and I outline several models of varying degrees of elegance in this SSRN paper here. But that's the big idea in a simple nutshell, and I don't find such a simple model ugly.