Customer Reviews

Quantitative Equity Portfolio Management: Modern Techniques and Applications (Chapman & Hall/CRC Financial Mathematics Series)

5 star:		(2)
4 star:		(2)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

Update after 1 month of reading:
(1) intially rated 4 stars, should be 5 stars (Good books are hard to find, language factor is minor)
(2) A serious Quant reader can gain a lot of insights from this book.
(3) Some of the discussions are way better than the other QEPM book(by Chincarini & Kim ). Although, this is half of the thickness.
(4) you need to be good with Linear Algebra. It is so much fun to see the authors use Linear equations to solve almost everything.

Short summary:
(1) Some advanced math background is needed (Linear Algebra mostly)
(2) Modern investment ideas are presented clearly.
(3) "Quant" book
(4) The Full 9 yards coverage from basic CAPM, alpha model, portfolio construction, trading and turnover, to attribution.
(5) the non-native author(s) should get some help on the writing.

This is an advanced book for quantitative analyst. On the surface, it does not require special math skills to read, which is nice. But to fully appreciate the ideas, you still need a lot of math background.

Most explanations are clean and easy to understand, even with the sometimes annoying writing skills.

Coverage of the modern investment ideas are quite comprehensive and to the right depth. Going deeper could risk more than 1000 pages, less will risk being superficial. There are certain areas in the investment industry that is not covered in this book, including automatic trading, pattern recognition, Bayesian based analysis, macro investing strategies, and alternative investment strategies. Lightly mentioned behavior finance.

Overall, still a good book to have.

I never liked Grinold/kahn's super-dry book, admittedly a classic, so I was really glad to have found this book, which provides a practical in-depth look at the various techniques one could use in constructing and managing portfolios. One of the authors, Sorenson, is well-known in the field but all three authors did a good job putting together a coherent and highly usable volume. I'm halfway through and I can't wait to finish the second half. If you're interested in or practice quantitative portfolio managemetn I highly recommend this book as a practical reference.

This is the best book on the market on quantitative equity research and portfolio management. This book is written by three highly respected quant managers at one of the best buy-side quant firms, Panagora. It's a great book for both students who want to learn quant equity research and practitioners in this business. In addition to entry-level materials on how to build factor models, the authors also include a few more advanced topics about dynamic factor weighting, contextual modeling, portfolio construction with transaction costs, etc. It's very well written, rigorous yet still highly readable. This book was published in 2007, just before the quant crisis; therefore, it didn't cover those areas like how to deal with market crisis, macroeconomic regime shift, and the latest new databases/factors. It's much more practical than Grinold and Kahn's [1999] book and roughly at the same level as Chincarini and Kim [2006], which is another book I'd recommend.

This book provides a nice introduction to Quantitative Equity Portfolio Management. The Math is simple even for undergraduate students with basic knowledge of algebra, calculus and statistics - econometrics.

It is an A-Z approach.

The authors cover the fundamentals of Modern Portfolio Theory.

They describe in detail the various indices / criteria active managers use in the design, optimization and control of ("alpha") portfolio optimization models and in performance attribution.

They cover the topic of factor models in full detail. I really liked the various results that are reported concerning the performnce of many factor-based alpha models that can be used to estimate expected returns.

Portfolio's turnover and transaction costs are also covered.

Although the topic is not the kind of "rocket science" I found the book very useful for the design of portfolio optimization models.

Unfortunately, similar textbooks, share the characteristic of redundant material.