Rating: 
Summary: Mandatory reading for financial boffins, nerds, and geeks!
Review: Alexander's new book is essential reading for intellectual risk managers, quant traders, and quantitatively minded market analysts; Ph.D students in finance would probably also find the book both useful and inspiring.The book has two outstanding qualities that set it apart from its benchmark, ie the 'average' of serious finance books. #1. The book is refreshingly well written. Considering that the topics of finance and risk management are not that conducive to stylistic efforts, this book is a marvel of clarity. #2. Market modeling is a topic that in most financial institutions on both the sell and the buy sides does not receive as much attention as it deserves and requires. Don't we all know of seemingly sophisticated risk management departments that actually are quite simplistic in how they generate volatility scenarios? Or what about the often mindless cranking out of historically based VaR estimates without considering the risk characteristics of the current regime? The beauty of this book is that it discusses market modeling in relation to its uses in other risk analytical areas such as derivatives modeling and VaR analysis.
Rating:
Summary: All in one guide to statistical models in finance
Review: Allmost 500 pages of packed information on major statistical methods used in modern finance. So many books are predictable; this one is different. It manages to cover each topic in the original style of the author: motivating, practical and full of examples with comments on the pitfalls of implementation.
The highpoints are (i) a comprehensive and illuminating review of GARCH models, (ii)new applications of PCA to the generation of robust, positive semi-definite covariance matrices (orthogonal GARCH) and to the analysis of volatility smiles and (iii) cointegration models with application to the design of hedge fund strategies. These are three areas where Carol Alexander not only shows her deep knowledge of previous research but has also made her own original contributions.
This book should be a must for MSc students in finance and economics. It should also be a useful intoductory guide to seasoned practitioners who will benefit from its numerous and up to date references. The CD alone with its databases and numerous working examples is worth ten times the price of the book.
Rating:
Summary: MARKET MODELS
Review: As a Ph.D candidate in finance at the University of Quebec at Montreal (specializing in hedge funds), I believe that Market Models is the leading text in the area of financial data analysis. Professor Alexander is considered as the leader by many in this field. Her many years of experience on both sides of the Atlantic (over 10 years) in consulting on risk management and investment analysis with positions in highly respected banking firms has put together this little gem of a book (long awaited). Professor Alexander's emphasis is based on understanding concepts and implementing solutions. Her past books have been best sellers and are extensively used both in academia and by financial institutions. This book is the only one of its kind that deals with key techniques for selecting and developing models, while using the latest insights into the pricing and hedging of options. At the same time the book focuses on a linear algebraic approach as an important tool for the anlaysis of financial systems. The book nicely deals with traditional time series analysis and is explained using 1)cointegration to long short equity hedge funds and 2) high frequency data prediction using neural networks. This book is a must read for academics, risk management specialists, money managers, analysts and others looking for a clear presentation of the subject. Congratulations on a great text. Hope a second volume is on the way.
Rating:
Summary: MARKET MODELS
Review: As a Ph.D candidate in finance at the University of Quebec at Montreal (specializing in hedge funds), I believe that Market Models is the leading text in the area of financial data analysis. Professor Alexander is considered as the leader by many in this field. Her many years of experience on both sides of the Atlantic (over 10 years) in consulting on risk management and investment analysis with positions in highly respected banking firms has put together this little gem of a book (long awaited). Professor Alexander's emphasis is based on understanding concepts and implementing solutions. Her past books have been best sellers and are extensively used both in academia and by financial institutions. This book is the only one of its kind that deals with key techniques for selecting and developing models, while using the latest insights into the pricing and hedging of options. At the same time the book focuses on a linear algebraic approach as an important tool for the anlaysis of financial systems. The book nicely deals with traditional time series analysis and is explained using 1)cointegration to long short equity hedge funds and 2) high frequency data prediction using neural networks. This book is a must read for academics, risk management specialists, money managers, analysts and others looking for a clear presentation of the subject. Congratulations on a great text. Hope a second volume is on the way.
Rating:
Summary: A Lucid Essential Reference
Review: Carol Alexander is a lucid writer and illustrator of financial models. It is a joy to find a book that is as well written as this with real-world examples. Professionals who need to refresh their model skills will make this their top book of choice. For modelers of credit derivatives needing good product descriptions, I highly recommend Tavakoli's book "Credit Derivatives and Synthetic Structures".
Rating:
Summary: A Great Guide for Building of Financial Market Models
Review: Carol Alexander's book does an excellent job of combining many of the disparate modelling techniques currently used in the financial markets while also providing many helpful real world examples. It thus successfully combines theory and application. The book is accessible to different types of users as it includes both in-depth qualitative analysis as well as quantitative ones. I have found it very useful in my work when trying to understand different concepts in the financial market models. Personally, I believe the book is a helpful tool one does not want to pass up--not only for the ones involved in risk measurement, but also for those in the more general field of investment banking as myself.
Rating: 
Summary: Comprehensive, lack in depth and poor organization
Review: For a starter, this book does offer a broad spectrum of subjects, volatility/variance measurement, PCAs, Factor Models, Time Series analysis, high frequency data modeling, etc, at the expense of rigor and depth.
Desipite the academic pedigree the author enjoys and the educational career she had, the book is rather poorly organized from a pedagogical point of view. She seems to have a tendency to refer to expressions, notions, ideas, data which appear much later than where the reference takes place. This makes first-timers cringe as they go through the chapters as they are laid out. It reads much like some published papers got dumbed down, and bundled together.
If you are looking for comprehensive introduction, without the gory details of mathematical mumblejumble, this book might be of help. But it may not be used as a reference book, for its organization and for its lack of rigor.
Rating: 
Summary: Nice book
Review: I will consider this book as a good introduction to different ways to analyze market data (covering mainly equity but do touch on fixed income as well as currency). I would emphasize that the book model the market more from an empirical point of view. The author gives a good description of the GARCH model as well as PCA analysis. Being a fixed income derivatives trading, I find both sections particularly useful for real world trading. The risk modeling section should expand into topics other than VAR such as coherent risk measures which are more useful. The co-integration section is a must for any traders who want to trade mean-reversion or stats arbitrage. Overall, I think that the book covers all basic to intermediate mathematics, econometrics and finance necessary for anyone who wants to model market data. The book explains how to use such model for trading, risk management as well as market data visualization / understanding.
Rating:
Summary: A buy you'll be happy you made.
Review: I'm a student of Carol Alexander at the ISMA Centre. This could set a bias, but I have tried in my review to be as objective as I possibly can.
Having covered with academic rigor 9 out of the 13 chapters of "market models", the only way i could describe it is as an excellent toolbox for financial modelling and a precise application to these tools to Risk measurement. One of the main features that make this book stand out of the crowd of similar books is the fact that it's paved with illustrations using real market data. You get a feel of the reality, not just some conceptual approach that might or might not work. The other feature that gives this book a step ahead of others is how Carol managed to make it perfectly accessible to someone with little mathematical weapons, yet kept it absolutely worth for the Quant! The constant but constructive analysis of the "practical" limitations and advantages of such and such models explained or mentioned, adds to keeping the whole scene of the book very realistic. It's also a true solutions book; it doesn't just tell you what to do by presenting the theory behind the concept, but how to do it by applying it to real data. Chapters like "principal components" and ["Non Normal Models" or Normal mixtures" as she likes to call them], bring forward some elegant, yet powerful and straightforward methods for modelling in finance. Market Models should be a trader's must read and without a doubt, "THE" book of the modern Risk Manager. Go get the book and learn what you need to know!
Rating:
Summary: Worth the money
Review: If you are looking for detailed rigorous mathematical development then look elsewhere, that is not the reason to purchase this book. It is targeted towards application and there it excels. I have not seen any other book on this topic that so effectively presents a level-headed applied approach that keeps the basic assumptions of the models firmly in sight.
What tool fits when is nicely discussed.
| 
