Market Risk Analysis, Quantitative Methods in Finance

I have studied this book cover-to-cover, and I dare to say it is the best book from which to learn or review the math foundations used in quantitative finance (financial econometrics and derivatives pricing). I only have a degree of bachelor of science in computer science, with two years of analysis-lite calculus courses plus a one-semester calculus-based probability class, from the University of Toronto back in 1999, and I was able to understand most of this book. I also have very limited amount of time to study (basically just one half hour each week day on BART ride).For someone with a similar background and time constraint as mine, Professor Alexander succinctly presents the foundational concepts of differentiation, integration, matrix algebra, multivariate probability, statistical inference, numerical methods, and portfolio theory. I had been searching for and could not find another book that covers so much ground in a single volume. Books like Mathematics for Economists (which I also highly recommend) do cover some of the maths, but do so from the perspectives of economics, not finance. Furthermore, they do not cover probability and statistics.Contrary to what some other reviewers say, I think the use of Excel in the book is one of its best features. The company where I work uses SAS, S-PLUS, R, Matlab and Gauss, so I do have access to these tools. However, not everyone, especially those who are not working at a financial company, is so fortunate. Even though R is open source, it would add another learning curve on top of what is already a formidable challenge. Excel can be considered as the lowest common denominator, and if an algorithm can be implemented in it, you can bet that it can be ported to any other tool. Professor Alexander's avoidance of VBA is also greatly appreciated, as it would just add another layer of unnecessary complexity.The only thing I miss from this book is more proofs or pointers to where we can find them. Don't get me wrong, this book is both practical and mathematically rigorous, and contains proofs or derivations for many theorems. However, probably due to the lack of space, a number of theorems are stated but not proved. For example, I would love to see more substantiation on why the t distributions are used for inferences on means and why the F distributions are for variance (section I.3.3.8). The standard I use to measure the clarity and completeness (in terms of proving from first principles) of other math books is Calculus by Professor Michael Spivak and Mathematical Statistics for Economics and Business by Professor Ron Mittelhammer (both of which I highly recommend; I am only half-way through the latter though). Having said that, Professor Alexander's book is probably as complete as anyone can make it with so few pages.There are a number of gems of distilled insight throughout the book that I have not found elsewhere, such as the difference in notations of price between discrete and continuous times (section I.1.4.1) and the difference between "estimation" and "calibration" of models (p. 201). Professor Alexander's quality of being a great teacher and mentor shines through these examples. I wish I could be her student at the ICMA. In a way, I already am.In summary, I cannot recommend this book highly enough for anyone who is starting to venture into the world of quantitative finance. I have already bought the rest of the volumes (save for volume IV, which is still unpublished) in the series, and I truly look forward to learning from them.Congratulations, Professor Alexander, for writing this outstanding text.

I have read a great deal of the books on credit and market risk. In Market Risk Analysis I, Prof. Alexander begins explaining concisely and accurately the core of the essential topics in the subject, in down-to-earth terms, and at all times with the reader in mind. Having said that, I would also like to point out that the author takes the reader through the chapters (always with a lot of examples) building knowledge as the text goes from a theoretical to a practical point of view, covering all you need to learn about the subject in an introductory work. This is an excellent book for practitioners and great mathematical education for finance students.

Guys, the book is just great. In fact all the series is great. For people like me who are into Risk the series is a must. Clear, concise and straightforward but well rounded approach to market risk. Highly recommended.

Nice product.

Prof. Carol has done a great job elucidating the finer concepts of Quant Finance in an intuitive way. By no means this is an elaborate text rather a premier on quant finance with good level of depth and emphasis on key themes. The reader would be best served to go through Hull before reading the text to maximize the benefits. The style is terse & conversant than pedantic and the author's mathematical fluency packs a punch.A definite buy & good resource to have on the shelf !

page26, the holdings for assets 1 and 2 are supposed to be rebalanced and kept to the original mix, 60% of current portfolio value for 1, and 40% for 2. However, the holdings on this page are based on the initial portfolio value, which is $100,000 in 2003.Is this the way it's supposed to be or a typo?

Although the topics covered are excellent and there are numerous illustrative examples are included (which I found extremely useful), there is a great deal of inconsistency in the notation (randomly changing indices for example) that are at best annoying and I could imagine would prove to be very confusing for a beginner.

Professor Alexander has done it once again with this wonderful gem of a book. This quantiative methods text no doubt will become standard issue in the industry. The book can assist risk managers, money manager, etc... a must for everyone working on Wall Street. This book should also help CFA students. CFA students would be wise to add this book to their collections. Congratulations on the 4 volume set and this book!Greg N. Gregoriou, PhDProfessor of FinanceState University of New York (Plattsburgh)