Performance Evaluation and Attribution of Security Portfolios
- 1st Edition - December 17, 2012
- Authors: Bernd R. Fischer, Russ Wermers
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 7 4 4 4 8 3 - 3
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 9 2 6 5 2 - 0
Just how successful is that investment? Measuring portfolio performance requires evaluation (measuring portfolio results against benchmarks) and attribution (determining… Read more
Just how successful is that investment? Measuring portfolio performance requires evaluation (measuring portfolio results against benchmarks) and attribution (determining individual results of the portfolio's parts), In this book, a professor and an asset manager show readers how to use theories, applications, and real data to understand these tools. Unlike others, Fischer and Wermers teach readers how to pick the theories and applications that fit their specific needs. With material inspired by the recent financial crisis, Fischer and Wermers bring new clarity to defining investment success.
- Gives readers the theories and the empirical tools to handle their own data
- Features practice problems formerly from the CFA Program curriculum.
Financial economics MA, MBA, and Ph.D. students studying asset pricing, portfolio management, financial management, and risk management
Introduction to the Series
Preface
Section 1: Performance Evaluation
Chapter 1. An Introduction to Asset Pricing Models
1.1 Historical Asset Pricing Models
1.2 The Beginning of Modern Asset Pricing Models
1.3 Efficient Markets
1.4 Studies That Attack the CAPM
1.5 Does proving the CAPM wrong = Market inefficiency? Or, do efficient markets = the CAPM is correct?
1.6 Small Capitalization and Value Stocks
1.7 The Asset Pricing Models of Today
1.8 Chapter-End Problems
References
Chapter 2. Returns-Based Performance Evaluation Models
2.1 Introduction
2.2 Goals, Guidelines, and Perils of Performance Evaluation
2.3 Returns-Based Analysis
2.4 Chapter-End Problems
References
Chapter 3. Returns-Based Performance Measures
3.1 Introduction
3.2 Luck vs. Skill
3.3 The Ultimate Goal of Performance Measures
3.4 Two Non-Regression Approaches
3.5 Regression-Based Performance Measures
3.6 Chapter-End Problems
References
Chapter 4. Portfolio-Holdings Based Performance Evaluation
4.1 Introduction
4.2 Unconditional Holdings-Based Performance Measurement
4.3 Conditional Holdings-Based Performance Measurement
4.4 Chapter-End Problems
References
Chapter 5. Combining Portfolio-Holdings-Based and Returns-Based Performance Evaluation (and the “Return Gap”)
5.1 Introduction
5.2 Performance-Decomposition Methodology
5.3 Application to U.S. Domestic Equity Mutual Funds
5.4 Empirical Results for U.S. Domestic Equity Mutual Funds
5.5 Results for U.S. Domestic Corporate BOND Mutual Funds
5.6 Appendix A
5.7 Appendix B
5.8 Chapter-End Problems
References
Chapter 6. Performance Evaluation of Non-Normal Portfolios
6.1 Introduction
6.2 Bootstrap Evaluation of Fund Alphas
6.3 Data
6.4 Results for U.S. Equity Funds
6.5 Sensitivity Analysis
6.6 Performance Persistence
6.7 Chapter-End Problems
References
Chapter 7. Fund Manager Selection Using Macroeconomic Information
7.1 Introduction
7.2 A Dynamic Model of Managed Fund Returns
7.3 Empirical Example: U.S. Domestic Equity Fund Data
7.4 Empirical Example: Results for U.S. Domestic Equity Funds
7.5 Chapter-End Problems
Appendix A Description of Mutual Fund Database
Appendix B Investments when fund risk loadings and benchmark returns may be predictable
Appendix C Investments when skills may be predictable
References
Chapter 8. Multiple Fund Performance Evaluation: The False Discovery Rate Approach
8.1 Introduction
8.2 The Impact of Luck on Managed Fund Performance
8.3 An Empirical Example: U.S. Domestic Equity Mutual Funds
8.4 An Empirical Example: Results for U.S. Domestic Equity Funds
References
Chapter 9. Active Management in Mostly Efficient Markets: A Survey of the Academic Literature
9.1 Introduction
9.2 Some Caveats
9.3 Does Active Management Add Value?
9.4 Active Management and “Mostly Efficient Markets”
9.5 Identifying Superior Active Managers (‘SAM’s)
9.6 Conclusions
9.7 Chapter-End Problems
References
Section 2: Performance Analysis and Reporting
Chapter 10. Basic Performance Evaluation Models
10.1 Basis Formula for the Calculation of Returns
10.2 Geometric Linkage and Scaling of Returns
10.3 Internal Rate of Return
10.4 Time-Weighted Return
10.5 Comparison Between the Time-Weighted Return and the Internal Rate of Return
10.6 Approximation Methods for the Computation of the Time-Weighted Return
10.7 Active Return
10.8 Continuously Compounded Returns
Appendix A Equality between the Time-Weighted Return and the Internal Rate of Return
Appendix B Solving Polynomial Equations for the Determination of Internal Rate of Return
Appendix C Time-Weighted Return and the Unit Price Method
Chapter 11. Indices and the Construction of Benchmarks
11.1 Basic Concepts
11.2 Equity Indices
11.3 Bond Indices
11.4 Money Market Indices
11.5 Peer Group Comparisons and Fund Universes
11.6 Benchmarks for Portfolios Investing in Multiple Asset Classes
11.7 Chapter-End Problems
Chapter 12. Attribution Analysis for Equity Portfolios According to the Brinson Approach
12.1 Introduction to Attribution Analysis
12.2 Single-Period Attribution Analysis According to the Brinson Approach
12.3 Multi-period Attribution Analysis According to Brinson et al.
12.4 Attribution Analysis in a Geometric Form
12.5 Further Aspects of Attribution Analysis
Chapter 13. Attribution Analysis for Fixed Income Portfolios
Appendix: Duration Measures
13.5 Exercises for Chapter-End Problems
Chapter 14. Analysis of Multi-Asset Class Portfolios and Hedge Funds
14.1 Basic Considerations
14.2 Attribution Analysis on Two Levels
14.3 Attribution Analysis on Three Levels
14.4 Implementation in practice
14.5 Risk-Adjusted Attribution Analysis Based On the Systematic Risk
14.6 Risk-Adjusted Attribution Analysis Based on the Information Ratio
14.7 Special Aspects in the Analysis of Hedge Funds
14.8 Chapter-End Problems
Chapter 15. Attribution Analysis with Derivatives
15.1 Attribution Analysis with Derivative-Based Currency Management
15.2 Treatment of Futures and Forwards
15.3 Treatment of Options
15.4 Swaps
15.5 Chapter-End Problems
Chapter 16. Global Investment Performance Standards (GIPS)
16.1 Background
16.2 Definition of Firm
16.3 Creation of Composites
16.4 Determination of Composite Return
16.5 Further Disclosure Requirements for Composite Structure and Sample Presentations
16.6 Maintenance of Composites
16.7 Independent Verification of Compliance with the Standards
16.8 Measurement of the Homogeneity of the Investment Process
16.9 Presentation of Risks according to the GIPS
16.10 Chapter-End Problems
Index
- Edition: 1
- Published: December 17, 2012
- Language: English
BF
Bernd R. Fischer
Bernd Fischer has occupied various high profile positions including Managing Director of IDS GmbH - Analysis and Reporting Services (a subsidiary of Allianz SE), one of the largest internationally operating providers of operational investment controlling services for institutional investors and asset managers; he was Global Head of Risk Controlling and Compliance in the central business segment Asset Management of Commerzbank AG and was also responsible for the operational Risk and Performance Controlling division of Cominvest GmbH. Between 2000 and 2004, he was a member of the CFA Institute's Investment Council. Since 2020, he has worked as an independent writer, covering political, cultural and economic topics for renowned German journals and blogs.
Affiliations and expertise
Managing Director of IDS GmbH, Analysis and Reporting Services (a subsidiary of Allianz SE), Frankfurt, GermanyRW
Russ Wermers
Russ Wermers is the Paul J. Cinquegrana '63 Endowed Chair in Finance and Director of the Center for Financial Policy (CFP) University of Maryland at College Park. His research, published in leading scholarly journals, has developed new approaches to measuring and attributing the performance of mutual funds, pension funds, and private equity funds, which, among other applications, can be used to identify superior active funds. Professor Wermers consults for the asset management industry. He received his Ph.D. from the University of California, Los Angeles, in December 1995.
Affiliations and expertise
Associate Professor of Finance, Smith School of Business, University of Maryland, USARead Performance Evaluation and Attribution of Security Portfolios on ScienceDirect