Table Of ContentPerformance
Evaluation and Attribution
of Security Portfolios
Introduction
to the Series
The aim of the Handbooks in Economics series is to produce Handbooks for var-
ious branches of economics, each of which is a definitive source, reference, and
ii
teaching supplement for use by professional researchers and advanced graduate
students. Each Handbook provides self-contained surveys of the current state of
a branch of economics in the form of chapters prepared by leading specialists on
various aspects of this branch of economics. These surveys summarize not only
received results but also newer developments, from recent journal articles and
discussion papers. Some original material is also included, but the main goal is
to provide comprehensive and accessible surveys. The Handbooks are intended
to provide not only useful reference volumes for professional collections but also
possible supplementary readings for advanced courses for graduate students in
economics.
KENNETH J. ARROW and MICHAEL D. INTRILIGATOR
Performance
Evaluation and Attribution
of Security Portfolios
by
Bernd Fischer and Russell Wermers
Academic Press is an imprint of Elsevier
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First edition 2013
Copyright © 2013 Elsevier Inc. All rights reserved
SOLNIK, BRUNO, McLEAVEY, DENNIS, GLOBAL INVESTMENTS, 6th Edition, © 2009,
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12 13 14 15 16 10 9 8 7 6 5 4 3 2 1
Preface
v
This book is intended to be the scientific state-of-the-art in performance evaluation—the
measurement of manager skills—and performance attribution—the measurement of all
of the sources of manager returns, including skill-based. We have attempted to include the
best and most promising scientific approaches to these topics, drawn from a voluminous
and quickly expanding literature.
Our objective in this book is to distill hundreds of both classic and the best cutting-
edge academic and practitioner research papers into a unified framework. Our goal is
to present the most important concepts in the literature in order to provide a directed
study and/or authoritative reference that saves time for the practitioner or academic
researcher. Sufficient detail is provided, in most cases, such that the investment
practitioner can implement the approaches with data immediately, without consulting
the underlying literature. For the academic, we have provided enough detail to allow an
easy further study of the literature, as desired.
We have contributed in two dimensions in this volume—both of which, we believe,
are missing in currently available textbooks. Firstly, we provide a timely overview
of the most important performance evaluation techniques, which allow an accurate
assessment of the skills of a portfolio manager. Secondly, we provide an equally timely
overview of the most important and widely used performance attribution techniques,
which allow an accurate measure of all of the sources of investment returns, and which
are necessary for precise performance reporting by fund managers.
We believe that our text is timely. An estimated $71.3 trillion was invested in managed
portfolios worldwide, as of 2009 (source: www.thecityuk.com). Managing this money,
thus, is a business that draws perhaps $700 billion per year in management fees and
other expenses for asset managers, in addition to a perhaps similar magnitude in annual
trading costs accruing to brokers, market makers, and other liquidity providers (i.e., Wall
Street and other financial centers). Our book is the first comprehensive text covering the
latest science of measuring the main output of portfolio managers: their benchmark-
relative performance (alpha). Our hope is that investors use these techniques to
improve the allocation of their money, and that portfolio management firms use them
to better understand the quality of their funds’ output for investors.
We intend this book to be used in at least two ways:
First, as a useful reference source for investment practitioners—who may wish to read
only one or a few chapters. We have attempted to make chapters self-contained to meet
this demand. We have also included chapter-end questions that both test the reader’s
vi Preface
understanding and provide examples of applications of each chapter’s concepts. The
audience for this use includes (at least) those studying for the CFA exams; performance
analysts; mutual fund and pension fund trustees; portfolio managers of mutual funds,
pension funds, hedge funds, and fund-of-funds; asset management ratings companies
(e.g., Lipper and Morningstar); quantitative portfolio strategists, regulators, financial
planners, and sophisticated individual investors.
Second, the book serves as an efficient way for mathematically advanced undergraduate,
masters, or Ph.D. students to undertake a thorough foundation in the science of
performance evaluation and attribution. After reading this book, students will be
prepared to handle new developments in these fields.
We have attempted to design each chapter of this book to contain enough detail to
bring the reader to a point of being able to apply the concepts therein, including the
chapter-end problems. In cases where further detail may be needed, we have cited the
most relevant source papers to allow further reading.
We have divided our book into two sections:
Part 1 of the book covers the area of performance evaluation.
Chapter 1 provides a short overview of the basics of empirical asset-pricing as applied
to performance assessment, including basic factor models, the CAPM, the Fama-French
three-factor model and the research on momentum, and the characteristic-based stock
benchmarking model of Daniel, Grinblatt, Titman, and Wermers.
Chapter 2 provides an overview of returns-based factor models, and the issues involved
in implementing them. Chapter 3 discusses the issue of luck vs. skill in generating
investment returns, and presents the fundamental performance evaluation measures,
including those based on the Chapter 2 factor models. In addition, extensions of these
factor models are introduced that contain factors that capture the ability of portfolio
managers to time the stock market or to time securities over the business cycle.
Chapter 4 presents the latest approaches to using portfolio holdings to more precisely
measure the skill of a portfolio manager. Chapter 5 provides a complete system for
evaluating the skills of a portfolio manager using her portfolio holdings and net returns.
Many managed portfolios generate non-normal returns. Chapter 6 shows how to apply
bootstrap techniques to generate more precise estimates of the statistical significance of
manager skills in the presence of non-normal returns and alphas.
Chapter 7 covers a very new topic: how to capture the time-varying abilities of a
portfolio manager (as briefly introduced in Chapter 3). Specifically, this chapter shows
how to predict which managers are most likely to generate superior alphas in the
current economic climate.
Chapter 8 also covers a very recent topic in performance evaluation: the assessment of
the proportion of a group of funds that are truly skilled using only their net returns.
This approach is very useful in assessing whether the highest alpha managers are truly
skilled, or are simply the luckiest in a large group of managers.
Preface vii
Finally, Chapter 9 is a “capstone chapter,” in that it provides an overview of the research
findings that use the principles outlined in the first 8 chapters. As such, it is a very useful
summary of what works (and what does not) when looking for a superior asset manager
(a “SAM”) and trying to avoid an inferior asset manager (an “IAM”).
Part 2 of the book primarily concerns performance attribution and related topics.
Since attribution analysis has become a crucial component within the internal control
system of investment managers and institutional clients, ample space is dedicated to a
thorough treatment of this field. The focus in this part lies on the practical applications
rather than on the discussions of the various approaches from an academic point of
view. This (practitioner’s) approach is accompanied by a multitude of examples derived
from practical experience in the investment industry. Great emphasis was also put
on the underlying mathematical detail, which is required for an implementation in
practice.
Chapter 10 provides an overview of the basic approaches for the measurement of
returns. In particular, the concepts of time-weighted return and internal rate of return, as
well as approximation methods for these measures are discussed in detail.
Attribution analysis, in practice, requires a deep understanding of the benchmarks
against which the portfolios are measured. Chapter 11 provides an introduction to the
benchmarks commonly used in practice, and their underlying concepts.
Chapter 12 covers fundamental models for the attribution analysis of equity portfolios
developed by Gary Brinson and others. Furthermore, basic approaches for the treatment
of currency effects and the linkage of performance contributions over multiple periods
are considered.
Chapter 13 contains an introduction to attribution analysis for fixed income portfolios
from a practitioner’s point of view. The focus lies on a methodology that is based on a
full valuation of the bonds and the option-adjusted spread. In addition, various other
approaches are described.
Based on the methodologies for equity and fixed income portfolios, Chapter 14 presents
different methodologies for the attribution analysis of balanced portfolios. This chapter
also illustrates the basic approaches for a risk-adjusted attribution analysis and covers
specific aspects in the analysis of hedge funds.
Chapter 15 describes the various approaches for the consideration of derivatives within
the common methodologies for attribution analysis.
The final chapter (Chapter 16) deals with Global Investment Performance Standards, a
globally applied set of ethical standards for the presentation of the performance results
of investment firms.
The authors are indebted to many dedicated academic researchers and tireless
practitioners for many of the insights in this book. Professor Wermers wishes to thank
the many investment practitioners that have provided data or insights into the topics
viii Preface
of this book, including through their professional investment management activities:
Robert Jones of Goldman Sachs Asset Management (now at System Two and Arwen),
Rudy Schadt of Invesco, Scott Schoelzel and Sandy Rufenacht of Janus (now retired,
and at Three Peaks Capital Management, respectively), Bill Miller and Ken Fuller
of Legg-Mason, Andrew Clark, Otto Kober, Matt Lemieux, Tom Roseen, and Robin
Thurston of Lipper, Don Phillips, John Rekenthaler, Annette Larson, and Paul Kaplan of
Morningstar, Sean Collins and Brian Reid of the Investment Company Institute.
Professor Wermers also wishes to thank all of the classes taught on performance
evaluation and attribution since 2001—at Chulalongkorn University (Bangkok);
the European Central Bank (Frankfurt); the Swiss Finance Institute/FAME Executive
Education Program (Geneva); Queensland University of Technology (Brisbane);
Stockholm University; the University of Technology, Sydney; and the University of
Vienna. Special thanks are due to students in that first class of the SFI/FAME program
during those dark days in September 2001, 10 days after the 9-11 attacks.
Professor Wermers is also indebted to his loving family, Johanna, Natalie, and
Samantha, for the endless hours spent away from them while preparing and teaching
this subject. He gratefully acknowledges Thomas Copeland and Richard Roll of UCLA
and Josef Lakonishok of University of Illinois (and LSV Asset Management) for early
inspiration, as well as Wayne Ferson, Robert Stambaugh, Lubos Pastor, and Mark
Carhart for their recent contributions to the field. In addition, he owes his career to the
brilliant mentoring of Mark Grinblatt and Sheridan Titman at UCLA, pioneers in the
subject of performance evaluation. This text would not have been possible from such
humble beginnings without their selfless support and guidance.
Dr. Fischer is indebted to his colleagues at IDS GmbH—Analysis and Reporting Services,
an international provider of operational investment controlling services. Over the
past years he has greatly benefited from numerous discussions surrounding practical
applications.
Thanks are also due to Dr. Fischer’s former team members at Cominvest Asset
Management GmbH. The design and the implementation of a globally applicable
attribution software from scratch, and the implementation of the Global Investment
Performance Standards were exciting experiences which left their mark on the current
treatise.
He also wishes to thank various colleagues (Markus Buchholz, Detlev Kleis, Ulrich
Raber, Carsten Wittrock, and others), with whom he co-authored papers in the past.
Several sections in this book are greatly indebted to the views expressed there.
Dr. Fischer is also indebted to the CFA institute and the Global Investment Performance
Committee for formative discussions surrounding the draft of the GIPS in 1998/1999
and during his official membership term from 2000 to 2004.
Both authors wish to thank J. Scott Bentley of Elsevier, whose vision it was to create such
a book, and whose patience it took to see it through.
To those whose contributions we have overlooked, our sincere apologies; such an
ambitious undertaking as condensing a huge literature necessitates that the authors
Preface ix
choose topics that are either most familiar to us or viewed by us as most widely useful.
Surely, we have missed some important papers, and we hope to have a chance to create a
second edition that expands on this one.
Finally, to the asset management practitioner: we dedicate this volume to you, and
hope that it is useful in furthering your goal of providing high-quality investment
management services!
Chapter 1
An Introduction to Asset
Pricing Models
3
ABSTRACT
This chapter provides a brief overview of asset pricing models, with an emphasis Keywords
Asset Pricing
on those models that are widely used to describe the returns of traded financial
Models,
securities. Here, we focus on various models of stock returns and fixed-income
CAPM,
returns, and discuss the reasoning and assumptions that underlie the structure Factor Models,
of each of these models. Fama French
three-factor model,
Carhart four-factor
model,
DGTW stock
1.1 HISTORICAL ASSET PRICING MODELS
characteristics
Individuals are born with a sense of the perils of risk, and they develop men- model,
tal adjustments to penalize opportunities that involve more risk.1 For example, Estimating beta,
Expected return
farmers do not plant corn, which requires a great deal of rainfall (which may or
and risk.
may not happen), unless the expected price of corn at harvest time is sufficiently
high. Currency traders will not take a long position in the Thai baht and short
the U.S. dollar unless they expect the baht to appreciate sufficiently. In essence,
the farmer and the currency trader are each applying a “personal discount
rate” to the expected return of planting corn or investing in baht. The farmer’s
discount rate depends on his assessment of the risk of rainfall (which greatly
affects his total corn crop output) and the risk of a price change in the crop. The
currency trader’s discount rate depends on the relative economic health of Thai-
land and the U.S., and any potential government intervention against currency
1 Gibson and Walk (1960) performed a famous experiment that was designed to test for depth
perception possessed by infants as young as six months old. Infants were unwilling to crawl on a
transparent glass plate that was placed over a several-foot drop, proving that they possessed depth
perception at a very early age. Another inference which can be drawn from this experiment is that
infants already perceive physical risks and exhibit risk-averse behavior at a very early age (probably
before they are environmentally taught to avoid risk).
Performance Evaluation and Attribution of Security Portfolios. http://dx.doi.org/10.1016/B978-0-08-092652-0.00001-7
© 2013 Elsevier Inc. All rights reserved.
For End-of-chapter Questions: © 2012. CFA Institute, Reproduced and republished with
permission from CFA Institute. All rights reserved.
