Efficient Asset Management A Practical Guide to Stock Portfolio Optimization and Asset Allocation

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Format: Hardcover
Pub. Date: 1998-06-15
Publisher(s): Oxford University Press
List Price: $64.00

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Summary

The failure of optimized portfolios to meet their practical investment goals has prompted many portfolio managers to abandon optimization techniques for simpler alternatives to maximize asset value. Yet, according to financial expert Richard Michaud, readily available methods exist to help practitioners reduce instability and enhance the value of optimization--tools that the investment community has largely ignored. In his succinct new book, Michaud argues that the problems lies with the conventional perception of optimization as a numerical computation; this view has severely restricted the typical manager's understanding of inherent limitations--and resulted in optimized portfolios that frequently fall short of their potential. If, instead, managers approach optimization as a statistical estimation, Michaud argues, they can resolve many of the serious limitations. Michaud identifies and explains five powerful techniques--improved estimation, application of benchmark priors, integration of active forecasts, tests for efficiency, and tests for portfolio weights--that portfolio managers can use to reduce errors, increase precision, and enhance the value of seemingly optimized portfolios. He illustrates the impact of each method with a simple asset allocation problem. With its important implications for investment practice, Efficient Asset Management 's highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud updates the practice of optimization for modern investment management.

Author Biography


Richard Michaud is a senior vice president of Acadian Asset Management in Boston, a director of the Institute for Quantitative Research in Finance, and an editorial board member of the Financial Analysts Journal.

Table of Contents

Preface xiii
Chapter 1: Introduction
1(6)
Markowitz Efficiency
1(1)
An Asset Management Tool
2(1)
Traditional Objections
3(1)
The Most Important Limitations
3(1)
Resolving the Limitations of Mean-Variance Optimization
4(1)
Illustrating the Techniques
5(2)
Chapter 2: Classic Mean-Variance Optimization
7(16)
Portfolio Risk and Return
7(2)
Defining Markowitz Efficiency
9(1)
Optimization Constraints
9(1)
The Residual Risk-Return Efficient Frontier
10(1)
Computational Algorithms
10(1)
Asset Allocation versus Equity Portfolio Optimization
11(2)
A Global Asset Allocation Example
13(3)
Reference Portfolios and Portfolio Analysis
16(1)
Return Premium Efficient Frontiers
16(4)
Appendix: Mathematical Formulation of Mean-Variance Efficiency
20(3)
Chapter 3: Traditional Criticisms and Alternatives
23(10)
Alternative Measures of Risk
23(2)
Utility Function Optimization
25(1)
Multiperiod Investment Horizons
26(3)
Asset-Liability Financial Planning Studies
29(2)
Linear Programming Optimization
31(2)
Chapter 4: Understanding Mean-Variance Efficiency
33(8)
The Fundamental Limitations of Mean-Variance Efficiency
33(2)
Repeating Jobson and Korkie
35(1)
Implications of Jobson and Korkie Analysis
36(1)
The Statistical Character of Mean-Variance Efficiency
36(1)
Efficient Frontier Variance
36(1)
The Statistical Equivalence Region
37(2)
A Practical Investment Tool?
39(2)
Chapter 5: Portfolio Review and Mean-Variance Efficiency
41(8)
Portfolio Review and Statistical Inference
41(1)
Tests of Asset Pricing Models
41(1)
Heuristic Inference
42(1)
A Sample Acceptance Region
42(3)
Statistical Inference for a Target Efficient Portfolio
45(1)
Rank-Associated Efficient Portfolios
45(4)
Chapter 6: Portfolio Analysis and the Resampled Efficient Frontier
49(22)
Conceptual Portfolio Statistical Analysis
49(1)
Efficient Portfolio Statistical Analysis
49(6)
The Resampled Efficient Frontier
55(1)
True and Estimated Optimization Inputs
56(1)
Testing Resampled Efficiency
56(4)
Properties of Resampled Efficient Frontiers
60(1)
Resampled Efficient Frontier Range
61(1)
Caveats
61(1)
Conclusion
62(1)
Appendix: Resampled Efficiency Tests and Alternatives
63(8)
Chapter 7: Portfolio Revision and Confidence Regions
71(12)
Confidence Intervals and Regions
71(1)
Resampled Efficiency and Distance Functions
72(1)
Resampled Efficient Frontier Confidence Regions
73(2)
Simultaneous Confidence Intervals
75(1)
Examples of Simultaneous Confidence Intervals
76(1)
Ambiguity and Portfolio Efficiency
77(2)
Practical Considerations
79(1)
Appendix A: Confidence Region for the Sample Mean Vector
80(1)
Appendix B: Computing Confidence Regions and Simultaneous Intervals
81(2)
Chapter 8: Input Estimation and Stein Estimators
83(18)
Admissible Estimators
84(1)
Bayesian Procedures and Priors
84(1)
Four Stein Estimators
85(1)
James-Stein Estimator
85(1)
James-Stein Mean-Variance Efficiency
86(4)
James-Stein Estimator Test of Resampled and Mean-Variance Efficiency
90(3)
Frost-Savarino Estimator
93(1)
Covariance Estimation
94(2)
Stein Covariance Estimation
96(1)
Forecasting Stock Risk and Return
97(1)
Utility Functions and Input Estimation
97(1)
Ad Hoc Estimators
98(1)
Conclusions
98(1)
Appendix: Ledoit Covariance Estimation
99(2)
Chapter 9: Benchmark Active Asset Allocation
101(14)
Benchmark-Relative Active Asset Allocation
102(3)
Implied-Return Asset Allocation
105(4)
Comparing Implied-Return and Benchmark-Relative Frontiers
109(1)
Scaling and Implied Returns
109(3)
Roll's Analysis
112(1)
Additional Procedures
113(2)
Chapter 10: Investment Policy and Economic Liabilities
115(12)
Misusing Mean-Variance Efficiency
115(1)
Economic Liability Models
116(1)
An Example: Endowment Fund Investment Policy
117(1)
Pension Liabilities and Benchmark Optimization
117(1)
Limitations of Actuarial Liability Estimation
118(2)
Economic Significance of Variable Liabilities
120(1)
Economic Characteristics of Variable Liabilities
121(1)
An Example: Economic Liability Pension Investment Policy
122(4)
Conclusion
126(1)
Chapter 11: Return Forecasts and Mixed Estimation
127(6)
Asset Allocation and Ad Hoc Inputs
127(1)
Mixed Estimation Forecasts
128(1)
Mixed Estimation Asset Allocation Inputs
128(1)
Index-Relative Active Asset Allocation
128(2)
Benefits
130(1)
Equity Return Forecasts and Mixed Estimation
130(3)
Chapter 12: Avoiding Optimization Errors
133(8)
Scaling Inputs
133(2)
Financial Reality
135(1)
Liquidity Factors
135(1)
Constraints
135(1)
Biased Portfolio Characteristics
136(1)
Index Funds and Optimizers
137(1)
Optimization from Cash
138(1)
Forecast Return Limitations
139(1)
Conclusion
140(1)
Epilogue 141(2)
Bibliography 143(6)
Index 149

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