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Practical Portfolio Performance Measurement and Attribution
Performance measurement and attribution are key tools in informing investment decisions and strategies. Performance measurement is the quality control of the investment decision process, enabling money managers to calculate return, understand the behaviour of a portfolio of assets, communicate with clients and determine how performance can be improved.
Focusing on the practical use and calculation of performance returns rather than the academic background, Practical Portfolio Performance Measurement and Attribution provides a clear guide to the role and implications of these methods in today's financial environment, enabling readers to apply their knowledge with immediate effect.
Fully updated from the first edition, this book covers key new developments such as fixed income attribution, attribution of derivative instruments and alternative investment strategies, leverage and short positions, risk-adjusted performance measures for hedge funds plus updates on presentation standards. The book covers the mathematical aspects of the topic in an accessible and practical way, making this book an essential reference for anyone involved in asset management.
Focusing on the practical use and calculation of performance returns rather than the academic background, Practical Portfolio Performance Measurement and Attribution provides a clear guide to the role and implications of these methods in today's financial environment, enabling readers to apply their knowledge with immediate effect.
Fully updated from the first edition, this book covers key new developments such as fixed income attribution, attribution of derivative instruments and alternative investment strategies, leverage and short positions, risk-adjusted performance measures for hedge funds plus updates on presentation standards. The book covers the mathematical aspects of the topic in an accessible and practical way, making this book an essential reference for anyone involved in asset management.
- GenresFinance
384 pages, Hardcover
First published November 5, 2004
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Displaying 1 - 2 of 2 reviews
April 28, 2016
My boss gave me a copy of this book, since it is relevant to my work as a programmer. I had some knowledge about some of the more basic concepts -- annualization, arithmetic mean, geometric mean, etc. -- but a huge blind spot as far as holdings-based calculations and especially performance attribution. In fact, I was very skeptical that performance attribution could be calculated.
Bacon has convinced me that performance attribution is both solvable and useful. And Bacon goes far beyond that. The first chapters do a good job of discussing differences between money-weighted returns and time-weighted returns, arithmetic mean and geometric mean, annualization, what makes for good benchmarks, and other basic ideas. These concepts are well-presented, and the introductory material is easy-to-follow.
However, the chapter on risk -- which I believe is the last introductory chapter -- simply tries to cover too many calculations. Many calculations get a short one paragraph description, if that. And many are simply described as variants of others. For instance, I once worked with Thomas Becker, who is mentioned in the book as the creator of the pain index and pain ratio (on different teams; it's probably most accurate to simple say that we worked at the same company, and sometimes spoke in the halls). For the record, although the book doesn't say so, Becker always credits Aaron Moore as a co-creator of the pain index and pain ratio. The pain index is simply described as a variant of the ulcer index ("if the drawdowns are not squared then the resulting pain index is very similar to the Zephyr pain index in discrete form as proposed by Thomas Becker in 2006"), and the pain ratio is simply referred to as a generic reward-risk ratio with the pain index as the risk statistic.
There's also a reference to style beta, but the book never defines style benchmark. William Sharpe's style analysis is useful to know, but only loosely related to performance attribution.
The chapters on performance attribution are, again, easy to follow. And they convinced me that performance attribution is reasonable and not that hard to calculate. The last portion of the book covers ethical standards about how data should be reported.
I was especially pleased that Bacon does admit to having favorite calculations. Many similar books cover the same ground, but don't give any advice on which calculations are most credible, or measure the correct things, or are useful with other calculations, etc.
Bacon has convinced me that performance attribution is both solvable and useful. And Bacon goes far beyond that. The first chapters do a good job of discussing differences between money-weighted returns and time-weighted returns, arithmetic mean and geometric mean, annualization, what makes for good benchmarks, and other basic ideas. These concepts are well-presented, and the introductory material is easy-to-follow.
However, the chapter on risk -- which I believe is the last introductory chapter -- simply tries to cover too many calculations. Many calculations get a short one paragraph description, if that. And many are simply described as variants of others. For instance, I once worked with Thomas Becker, who is mentioned in the book as the creator of the pain index and pain ratio (on different teams; it's probably most accurate to simple say that we worked at the same company, and sometimes spoke in the halls). For the record, although the book doesn't say so, Becker always credits Aaron Moore as a co-creator of the pain index and pain ratio. The pain index is simply described as a variant of the ulcer index ("if the drawdowns are not squared then the resulting pain index is very similar to the Zephyr pain index in discrete form as proposed by Thomas Becker in 2006"), and the pain ratio is simply referred to as a generic reward-risk ratio with the pain index as the risk statistic.
There's also a reference to style beta, but the book never defines style benchmark. William Sharpe's style analysis is useful to know, but only loosely related to performance attribution.
The chapters on performance attribution are, again, easy to follow. And they convinced me that performance attribution is reasonable and not that hard to calculate. The last portion of the book covers ethical standards about how data should be reported.
I was especially pleased that Bacon does admit to having favorite calculations. Many similar books cover the same ground, but don't give any advice on which calculations are most credible, or measure the correct things, or are useful with other calculations, etc.
February 25, 2013
Excellent reference volume. Many of the functions described in the book have been implemented in the R library PerformanceAnalytics, so that makes it easy to experiment with. The appendices with the simple and multi-currency attribution models are also appreciated. Looking forward to seeing the second edition.
If I had one complaint, it would be the presentation of an involved methodology, followed by concluding remarks to the effect of "but this is cumbersome and clumsy." The value of this volume is as a reference for best practice, so if something is not best practice, I'd rather not have it cluttering up the pitch.
My self-assigned "book for work" for February.
If I had one complaint, it would be the presentation of an involved methodology, followed by concluding remarks to the effect of "but this is cumbersome and clumsy." The value of this volume is as a reference for best practice, so if something is not best practice, I'd rather not have it cluttering up the pitch.
My self-assigned "book for work" for February.
Displaying 1 - 2 of 2 reviews