Reviews 'This book is a must have for quantitative equity managers and it provides a step-by-step illustration of how to build a superior, repeatable investment process. By combining academic research with practical implementation considerations, the book outlines the theoretical foundation of various market anomalies such as value, momentum, quality, calendar effect, and analyzes their actual performance with real world portfolios under institutional setting. The book can also serve as a valuable text and reference for students and academic researchers in the field.

With rigorous mathematical analytics, the book goes beyond the traditional efficient frontier paradigm. For example, the objective of maximizing information ratio as a performance measure extends traditional academic research settings to make it more practically relevant.

Quantitative Equity Portfolio Management: Modern Techniques and Applications - CRC Press Book. Qian, Ronald H. Quantitative equity portfolio management combines theories and advanced techniques from several disciplines, including financial economics, accounting, mathematics. Tain monetary and fiscal policy responses. In this environment, some ofthe traditional static quantitative equity strategies have struggled, in part due to the perverse behavior of their quantitative factors. In a static quantitative model, the factor weightings are based on long-term risk- return statistics and show little change over.

This results in some subtle yet critical analytical insights regarding quantitative factors and strategies. In addition, the mathematical treatment of the nonlinear factor effect and contextual factor model is intuitive and based on fundamental understanding of the market dynamics.' -Li Jin, Assistant Professor of Finance, Harvard Business School, Boston, Massachusetts, USA 'Quantitative Equity Portfolio Management sets a new standard for comprehensive assessments of quantitative techniques.

The authors' experience as practitioners brings to light critical issues of implementation, such as transaction costs and turnover, which have not previously achieved sufficient attention. Overall, the depth, rigor, and elegance of the authors' approach to the topic make it a valuable resource for investment professionals everywhere.'

-Bruce MacDonald, Director, Asset Allocation and Risk Analysis, University of Virginia Investment Management Company, Charlottesville, USA 'Fans of Grinold and Kahn's standard text Active Portfolio Management will love the new book Quantitative Equity Portfolio Management by Qian, Hua, and Sorensen. It reflects the latest, most up-to-date thinking on portfolio theory, risk and alpha modeling, transaction costs, and multiperiod strategies. The authors are expert, proven practitioners of the art and active researchers in the field, and have provided an essential handbook covering both theory and many practical implementation issues not available in existing books. This is a must-have addition to the bookshelf of professional portfolio managers and students of portfolio management alike. I also expect this book will inspire faculty in quantitative finance and financial engineering to add more quantitative portfolio management to the usual option pricing material that students learn on their way to careers in the investments industry.' Kercheval, Associate Professor, Director of Financial Mathematics, Florida State University, Tallahassee, USA ' a superb book for the sophisticated investment practitioner.

It brings together rigorous derivation and practical insight across the complete spectrum of topics needed for an intelligent investment process. Most importantly, it brings forward detailed methodologies for dealing with subtle, but critical subjects such as alpha decay and optimal trading strategies that are beyond the scope of other texts.

For many of us in the field, our only regret about the book will be that we did not write it.' -Dan diBartolomeo, President, Northfield Information Services, Inc., Boston, Massachusetts, USA. CRC Press eBooks are available through VitalSource.

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Very few good practitioners’ cookbooks are available on quantitative equity portfolio management (QEPM). Ludwig Chincarini and Daehwan Kim’s book reduces this dearth.

No previous volume has combined depth and breadth on the subject in a unified framework by a single set of authors. A book of this type usually consists of articles by different authors with varying strengths, a fair amount of redundancy, and no consistent notation. Having just two authors is invaluable, especially when they possess a rare knack of writing about the practical aspects of quantitative equity investing in a clear style. While paying homage to the academic literature, Quantitative Equity Portfolio Management: An Active Approach to Portfolio Construction and Management focuses on how to get things done.

It does not shortchange the reader, however, on the technical aspects. After reading this work, all a practitioner will need to construct a quantitative-based portfolio is some statistical software and a database.

Naturally, there is a difference between reading a cookbook and becoming a chef, but readers of this book will know their way around the “quant kitchen.” Chincarini and Kim begin with seven basic tenets for quantitative investment that form a strong foundation for all their work: • Markets are mostly efficient. • Pure arbitrage opportunities do not exist. • Quantitative analysis creates statistical arbitrage opportunities. • Quantitative analysis combines all of the available information in an efficient way. • Quantitative models should be based on sound economic theories.

• Quantitative models should reflect persistent and stable patterns. • Deviations of a portfolio from the benchmark are justified only if the uncertainty is small enough. The first two tenets underscore the challenge of going up against market efficiency. Numbers 3–5 focus on the fundamental law of active management: The information ratio is related to the breadth of the portfolio manager’s universe and the information coefficient of trades. The final two tenets deal with statistical issues. Seldom do quantitative books clearly describe their underlying philosophical assumptions to their modeling approach in such an accessible manner.

Quantitative Equity Portfolio Management is divided into five parts. The first part lays out the fundamental assumptions of QEPM. Part 2 reviews portfolio construction and maintenance.

The third part, with the pithy title “Alpha Mojo,” shows how quantitative techniques can be used to enhance alpha generation. Part 4 provides information about performance analysis and attribution, and the final part discusses practical applications and real-life issues in portfolio management. Quant work is clearly not for everyone.

This book’s overview section discusses the advantages and disadvantages of QEPM as well as how a quantitative or qualitative analyst will look at similar situations differently. Together with providing the seven tenets for QEPM, the authors explain in great detail how the tenets apply to their thought processes. The tenets are supported with a breakdown of quantitative relationships that have been exploited in the past and that fit their criteria. For example, the authors provide a list of market anomalies and the references for research done in each area. Following the same procedure for behavioral influences, they describe the resulting biases and give examples. Some quantitative analysts may quibble with the composition of Chincarini and Kim’s lists, but the lists provide a good breakdown of the focal areas of quantitative methods and highlight the biases that systematic investing tries to minimize. Celestial Magic Nigel Jackson Pdf To Excel. The authors offer informative discussions of the difference between screening and ranking stocks and of the use of normalized Z-scores and fundamental values. Download Aplikasi Magic Blue Hack Android.

The authors also explain how various modeling approaches differ and provide a methodology for choosing the right model in a given situation. Although this support information is valuable, the book’s greatest benefit is a detailed structure for combining different approaches to QEPM, such as fundamental and economic factor analysis. The comparisons of these methods in Part 1 are rich in detail, although a more precise discussion of how to implement and test models would have been useful. Part 2 dives into the details of model building; the authors explain factor models and how to select factors. They divide the factors into categories to explain the choices. Their categories are valuation, solvency, operating efficiency, profitability, financial risk, liquidity, economics, and technical considerations.

The importance of choosing the right model and the econometric traps surrounding the selection of factors are often overlooked, yet these areas are where most investors encounter frustration. Also in this section, Chincarini and Kim describe procedures for using Z-scores to screen and rank stocks. The difference between fundamental and economic factors, as well as procedures for forecasting factor premiums and exposures, are explored in detail.

These clear descriptions relieve the reader of the need to go to an original source to obtain the specific steps on modeling. The presentation on forecasting factor premiums and parameter uncertainty is particularly clear and comprehensive. Understanding these aspects is essential if a reader wants to actually build usable models. The authors also discuss outliers and robustness testing of models. Construction of a portfolio through stock picking is integrated by the determination of portfolio weights under optimization with constraints. Issues of factor targeting and tracking error are addressed, but following up on “cookbook issues” of how to check the optimization would have been helpful.

The important practical aspects of rebalancing, transaction costs, and tax management are thoroughly addressed, which is unusual in a quantitative treatment but vital for actual portfolio management. Note that, although the book is comprehensive, a solid knowledge of regression analysis and optimization is needed to understand the presentation fully.

The devil is in the econometric details when striving for useful results. The book’s third part is a wide-ranging discussion of techniques for adding alpha. Construction of leveraged portfolios through derivatives is explained.

Market-neutral investing, which focuses on isolating alpha, is developed as an extension of factor modeling. The authors also provide a review of Bayesian techniques, which can be used in the search for alpha through setting prior probabilities. Although this specialized approach is interesting, I would have preferred the authors spending more time on the main topics to ground the reader thoroughly.

Part 4, dealing with performance analysis, tackles issues of measurement and attribution. This section could have been placed with the discussion of tracking error because a description of errors is essential in measuring performance. The book’s final part addresses such practical applications as backtesting, analyzing model performance, and real-life portfolio management issues, such as taxes and transaction costs. In addition, a CD-ROM of data and examples is provided. Throughout the book, the authors do a superb job of pointing out potential pitfalls with quantitative modeling. These complexities as well as extensions of the core principles are made through the end-of-chapter questions. Ordinarily, we would not look at a book’s end-of-chapter questions, but in this case, they effectively test the reader’s understanding of the key concepts.

Our only major criticism of Quantitative Equity Portfolio Management is that more practical examples would have been helpful. It is unusual, certainly, for a reader to ask for more of anything after plowing through 650 pages of quantitative material. Still, a cookbook needs specific instructions on how to turn a recipe into a palatable dish.

Furthermore, because so many topics are covered, a number of important issues have received only limited attention. A two-page treatment of a complex topic, such as forming the optimal portfolio with transaction costs, cannot provide all the details needed to generate an effective quantitative program.

Like any overview of a large subject, this one favors the authors’ preferences, yet the authors display little bias in their presentation of the material. Reading Quantitative Equity Portfolio Management in conjunction with Grinold and Kahn’s thorough 1999 explication of theory provides a powerful amalgamation of academic theory and practical reality. Practitioners who are serious about quantitative investing and want to focus on the details of running the numbers should have this book on their shelves. Notes 1The information ratio here is defined as the portfolio’s excess return over the return of its benchmark index divided by the tracking error.

Grinold and Kahn define the information ratio as expected active (excess) return divided by active risk. Breadth is the number of independent bets a portfolio manager can take, and the information coefficient is a measure of managerial skill—namely, the correlation between actual returns and the manager’s forecasts of returns. See Richard Grinold and Ronald Kahn, Active Portfolio Management, 2nd ed. (McGraw-Hill, 1999).