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A Practitioner's Guide to Asset Allocation

A Practitioner's Guide to Asset Allocation

by Harry M. Markowitz, David Turkington, Mark P. Kritzman, William Kinlaw
Publisher: Wiley
Release Date: May 2017
ISBN: 9781119397809
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Book Description

The authors' goal in writing this book is twofold: to describe several important innovations that address key challenges to asset allocation and to dispel certain fallacies about asset allocation. Section I covers the fundamentals of asset allocation, section II presents certain fallacies about asset allocation which the authors attempt to dispel either by logic or with evidence, section III discusses recent innovations, and section IV provides supplementary material.

Table of Contents

  1. Cover
  2. Title Page
  3. Foreword
  4. Preface
  5. SECTION One: Basics of Asset Allocation
    1. CHAPTER 1: What Is an Asset Class?
      1. STABLE AGGREGATION
      2. INVESTABLE
      3. INTERNALLY HOMOGENEOUS
      4. EXTERNALLY HETEROGENEOUS
      5. EXPECTED UTILITY
      6. SELECTION SKILL
      7. COST‐EFFECTIVE ACCESS
      8. POTENTIAL ASSET CLASSES
      9. REFERENCES
      10. NOTES
    2. CHAPTER 2: Fundamentals of Asset Allocation
      1. THE FOUNDATION: PORTFOLIO THEORY
      2. PRACTICAL IMPLEMENTATION
      3. REFERENCES
      4. NOTES
  6. SECTION Two: Fallacies of Asset Allocation
    1. CHAPTER 3: The Importance of Asset Allocation
      1. FALLACY: ASSET ALLOCATION DETERMINES MORE THAN 90 PERCENT OF PERFORMANCE
      2. THE DETERMINANTS OF PORTFOLIO PERFORMANCE
      3. THE BEHAVIORAL BIAS OF POSITIVE ECONOMICS
      4. THE SAMUELSON DICTUM
      5. REFERENCES
      6. NOTES
    2. CHAPTER 4: Time Diversification
      1. FALLACY: TIME DIVERSIFIES RISK
      2. SAMUELSON'S BET
      3. TIME, VOLATILITY, AND PROBABILITY OF LOSS
      4. TIME AND EXPECTED UTILITY
      5. WITHIN‐HORIZON RISK
      6. A PREFERENCE‐FREE CONTRADICTION TO TIME DIVERSIFICATION
      7. THE BOTTOM LINE
      8. REFERENCES
      9. NOTES
    3. CHAPTER 5: Error Maximization
      1. FALLACY: OPTIMIZED PORTFOLIOS ARE HYPERSENSITIVE TO INPUT ERRORS
      2. THE INTUITIVE ARGUMENT
      3. THE EMPIRICAL ARGUMENT
      4. THE ANALYTICAL ARGUMENT
      5. THE BOTTOM LINE
      6. REFERENCES
      7. NOTES
    4. CHAPTER 6: Factors
      1. FALLACY: FACTORS OFFER SUPERIOR DIVERSIFICATION AND NOISE REDUCTION
      2. WHAT IS A FACTOR?
      3. EQUIVALENCE OF ASSET CLASS AND FACTOR DIVERSIFICATION
      4. NOISE REDUCTION
      5. WHERE DOES THIS LEAVE US?
      6. REFERENCES
      7. NOTES
    5. CHAPTER 7: 1/N
      1. FALLACY: EQUALLY WEIGHTED PORTFOLIOS ARE SUPERIOR TO OPTIMIZED PORTFOLIOS
      2. THE CASE FOR 1/N
      3. SETTING THE RECORD STRAIGHT
      4. EMPIRICAL EVIDENCE IN DEFENSE OF OPTIMIZATION
      5. PRACTICAL PROBLEMS WITH 1/N
      6. BROKEN CLOCK
      7. THE BOTTOM LINE
      8. REFERENCES
      9. NOTE
  7. SECTION Three: Challenges to Asset Allocation
    1. CHAPTER 8: Necessary Conditions for Mean‐Variance Analysis
      1. THE CHALLENGE
      2. DEPARTURES FROM ELLIPTICAL DISTRIBUTIONS
      3. DEPARTURES FROM QUADRATIC UTILITY
      4. FULL‐SCALE OPTIMIZATION
      5. THE CURSE OF DIMENSIONALITY
      6. APPLYING FULL‐SCALE OPTIMIZATION
      7. SUMMARY
      8. REFERENCES
      9. NOTES
    2. CHAPTER 9: Constraints
      1. THE CHALLENGE
      2. WRONG AND ALONE
      3. MEAN‐VARIANCE‐TRACKING ERROR OPTIMIZATION
      4. REFERENCES
      5. NOTE
    3. CHAPTER 10: Currency Risk
      1. THE CHALLENGE
      2. WHY HEDGE?
      3. WHY NOT HEDGE EVERYTHING?
      4. LINEAR HEDGING STRATEGIES
      5. NONLINEAR HEDGING STRATEGIES
      6. ECONOMIC INTUITION
      7. REFERENCES
      8. NOTES
    4. CHAPTER 11: Illiquidity
      1. THE CHALLENGE
      2. SHADOW ASSETS AND LIABILITIES
      3. EXPECTED RETURN AND RISK OF SHADOW ALLOCATIONS
      4. OTHER CONSIDERATIONS
      5. CASE STUDY
      6. THE BOTTOM LINE
      7. APPENDIX
      8. REFERENCES
      9. NOTES
    5. CHAPTER 12: Risk in the Real World
      1. THE CHALLENGE
      2. END‐OF‐HORIZON EXPOSURE TO LOSS
      3. WITHIN‐HORIZON EXPOSURE TO LOSS
      4. REGIMES
      5. THE BOTTOM LINE
      6. REFERENCES
      7. NOTES
    6. CHAPTER 13: Estimation Error
      1. THE CHALLENGE
      2. TRADITIONAL APPROACHES TO ESTIMATION ERROR
      3. STABILITY‐ADJUSTED OPTIMIZATION
      4. BUILDING A STABILITY‐ADJUSTED RETURN DISTRIBUTION
      5. DETERMINING THE OPTIMAL ALLOCATION
      6. EMPIRICAL ANALYSIS
      7. THE BOTTOM LINE
      8. REFERENCES
      9. NOTES
    7. CHAPTER 14: Leverage versus Concentration
      1. THE CHALLENGE
      2. LEVERAGE IN THEORY
      3. LEVERAGE IN PRACTICE
      4. THE BOTTOM LINE
      5. REFERENCES
      6. NOTES
    8. CHAPTER 15: Rebalancing
      1. THE CHALLENGE
      2. THE DYNAMIC PROGRAMMING SOLUTION
      3. THE MARKOWITZ–VAN DIJK HEURISTIC
      4. THE BOTTOM LINE
      5. REFERENCES
      6. NOTES
    9. CHAPTER 16: Regime Shifts
      1. THE CHALLENGE
      2. PREDICTABILITY OF RETURN AND RISK
      3. REGIME‐SENSITIVE ALLOCATION
      4. TACTICAL ASSET ALLOCATION
      5. THE BOTTOM LINE
      6. APPENDIX: BAUM‐WELCH ALGORITHM
      7. REFERENCES
      8. NOTES
  8. SECTION Four: Addendum
    1. CHAPTER 17: Key Takeaways
    2. CHAPTER 18: Statistical and Theoretical Concepts
      1. DISCRETE AND CONTINUOUS RETURNS
      2. ARITHMETIC AND GEOMETRIC AVERAGE RETURNS
      3. STANDARD DEVIATION
      4. CORRELATION
      5. COVARIANCE
      6. COVARIANCE INVERTIBILITY
      7. MAXIMUM LIKELIHOOD ESTIMATION
      8. MAPPING HIGH‐FREQUENCY STATISTICS ONTO LOW‐FREQUENCY STATISTICS
      9. PORTFOLIOS
      10. PROBABILITY DISTRIBUTIONS
      11. THE CENTRAL LIMIT THEOREM
      12. THE NORMAL DISTRIBUTION
      13. HIGHER MOMENTS
      14. THE LOGNORMAL DISTRIBUTION
      15. ELLIPTICAL DISTRIBUTIONS
      16. PROBABILITY OF LOSS
      17. VALUE AT RISK
      18. UTILITY THEORY
      19. SAMPLE UTILITY FUNCTIONS
      20. ALTERNATIVE UTILITY FUNCTIONS
      21. EXPECTED UTILITY
      22. CERTAINTY EQUIVALENTS
      23. MEAN‐VARIANCE ANALYSIS FOR MORE THAN TWO ASSETS
      24. EQUIVALENCE OF MEAN‐VARIANCE ANALYSIS AND EXPECTED UTILITY MAXIMIZATION
      25. MONTE CARLO SIMULATION
      26. BOOTSTRAP SIMULATION
      27. REFERENCES
      28. NOTE
    3. CHAPTER 19: Glossary of Terms
  9. Index
  10. End User License Agreement