Customer Reviews

The Econometrics of Financial Markets

5 star:		(6)
4 star:		(5)
3 star:		(1)
2 star:		(1)
1 star:		(3)

 

 

I was also skeptical of the negative reviews surrounding this book ("CML"). However after buying and reading this book, I now believe they had merit.

Simply stated, this book does not cater to its readers. If you have the prerequisites that the authors demand, then this book is comprehensive but ultimately below what ought to challenge you. And if you don't, then I guarantee you will be very lost. Unlike many similar volumes, CML is not self-contained (nor does it claim to be). And unlike many books that build a self-contained "model" of asset pricing dynamics, CML is full of literature-specific jargon and inconsistent notation. In fact much of this notation changes intrachapter.

Suppose you are a reader at the level CML insist their readers be. Then all the better to spend more time understanding Duffie's "Dynamic Asset Pricing," or Cochrane's veritable tour-de-force, "Asset Pricing." Both books are more contemporary and also at a better level for the readers CLM had in mind.

If you don't have the requisite knowledge, please ignore CML and try Luenenberger and Casella/Berger, as well as Greene for econometric-specific stats, Hamilton for time-series. You will not regret these purchases.

CML claims to fill a gaping hole in the secondary literature. But in reality, CML sits right in the middle of two types of readers, and caters effectively to none.

This book seems to have written to cash in on the fame of the authors and the stampede in academia and industry towards financial econometrics.

The book already assumes you are proficent in basic and advanced econometrics, derivatives pricing, fixed income, microstructure, neural networks etc. If you already familiar with those fields, why do you need this book? For example, Chapter 10 on Fixed Income Securities covers a grand total of 28 pages beginning with "Basic Concepts" and ending with "Yield Spreads and Interest Rate forecasts". Meanwhile there are whole tomes devoted to every one of those sections in Chapter 10. Nonparameteric Estimation merits a grand total of 9 pages and Neural networks merits 7 pages in Chapter 12.

The chapter on Microstructure, virtue of the book being published in 1997 is thoroughly dated. Even for its 1997 publication the chapter is thoroughly lacking. It is neither a survey nor a exposition of theory or practial uses of microstructure theory. Today there are excellent theoretical and practical books devoted to every topic covered in this book.

Save your money for one of those.

This is a concise treatment of major foundation topics in financial economics. Although my interest is in monetary economics and macro, I finally have a book I will keep and use on financial economics. It closely blends the insight and "wisdom" behind the various theories with parsimonious amounts of math. Careful, patient reading and a comfortable grasp of econometrics is required but will be rewarded. Notation changes were a bit of a problem, though the authors address this issue early on. The end of chapter questions are good but it would've helped to have answers. Overall, it is intuitive "page turner" material.

This is really a classic book on financial econometrics. I like the design of the book. The content is also pretty up-to-date. A little bit advanced - requires solid background in econometrics, analysis, statistics, and some stochastic calculus. The only problem I have is the authors did not provide background data, so it's really hard for people to do self-study like me. If the authors could include a preferred computer program (i.e. Matlab, GAUSS, EViews, etc.) with codes and data, that will make the book a true bible of financial econometrics.

It takes time to work yourself through this book. The authors assume a good background in econometric theory. If you take your time though (a lot of time), you will like it. I was frustrated with it at first (it is my first econometrics book), but having spent a full semester with it, I now feel quite comfortable with the subject matter. This is not a book you can just read at night before you go to bed. This book needs to be studied carefully. Buy it only if you are a graduate student in econ or finance, or a practitioner in the field. This book is no fun and you will only read it (and learn to appreciate its depth) if you absolutely have to.

I just used this book in my master in finance course and think its very good but a bit outdated and incomplete. I was able to benefit from it, but only because of my previous strong finance, econometrics and computing knowledge. Without any of my skills i would be surely lost. The sad part is i cant remember another book filling its niche. Maybe only John Cochrane "Asset Pricing" overlaps well in some subjects.

The book outline the econometrics of major finance issues, but doesnt give detailed descriptions of main results. As an example, the Maximum likelihood formulas for multifactor asset pricing models are simply shown, but they dont explain how they got there (the likelihood function), so additional effort is needed if one wants to modify something - [A Critic : If you need to work on the econometrics of something yourself you dont need to buy the book, just learn finance and econometrics and put it together yourself !!]

The book maybe useful as a reference on many subjects, but to actually implement the models (as a practictioner or analyst) you will most likely need additional knowledge/books on a given subject. They also dont show any kind of algorithms/computing techniques or codes to do implement it, so you must be skilled enough at computing to crack it.

As an improving suggestion, the authors should reduce the number of chapters/subjects, completing it with more detailed formulas and computer codes/guides to actual implementation.

It covers a variety of topics in a very formal way. it is NOT an easy book (and it shouldn't be...) and it demonstrates that markets are NOT random. Enjoy it.

In recent years, the economist have used various econometric method in analyses financial market, but though you can discover some excellent book for financial theory,such as Darrell Duffie's "Dynamic Asset Pricing Theory",there is few comprehensive book on the theories and applications of econometric tools for emprirical finance. So when I found this book, I was so excited. Only having read several chapters, I think it an excellent book, though some difficult, and can't help to introduce it. I think every student who is interested in financial market should read it, at least scan it to know the content of this book. If you have this book, then you can throw all other book on this subject, don't waste time to read them, what you need is just this excellent book. Unfortunely I havn't it,and I hope to own it some day. At last, I have to say thank you to Prof. Gregory Chow who brough this book to my University, so I have chance to read such an excellent book.

It is a good book, but there are some aspects which I find lacking in the book which could be helpful. For example, brief outline answers to some of the problems at the end of the chapter will help most readers no doubt. Also, a more comprehensive cover on the rational bubbles and GARCH type models for asset returns will help no doubt, as well as problems that may arise during implementation. This book is aimed at the advance graduate student who is pretty proficient in theoretical finance and advance econometric issues already.

Finally, we have a book like this. It is comprehensive, not so hard to follow, and handsomely structured. It shows you the power of combination of mathematics, statistics, and finance. It is like beer. It makes you dizzy and enchanted simutaneously.

It stimulates you to dream of modeling the stock market and know the tomorrow's price of Amazon.com. At least, I am going to give it a try! You can have fun, make money, and look mysterious at the same time.

Review or learn the math and statistics courses necessary for the book. Read the book three times. Then, you are near the top of mountain.