A Practitioner's Guide to Asset Allocation by William Kinlaw,Mark P. Kritzman,David Turkington -- Read -- Imperial Library of Trantor

Index

Cover Title Page Table of Contents Foreword Preface SECTION One: Basics of Asset Allocation

CHAPTER 1: What Is an Asset Class?

STABLE AGGREGATION INVESTABLE INTERNALLY HOMOGENEOUS EXTERNALLY HETEROGENEOUS EXPECTED UTILITY SELECTION SKILL COST-EFFECTIVE ACCESS POTENTIAL ASSET CLASSES REFERENCES NOTES

CHAPTER 2: Fundamentals of Asset Allocation

THE FOUNDATION: PORTFOLIO THEORY PRACTICAL IMPLEMENTATION REFERENCES NOTES

SECTION Two: Fallacies of Asset Allocation

CHAPTER 3: The Importance of Asset Allocation

FALLACY: ASSET ALLOCATION DETERMINES MORE THAN 90 PERCENT OF PERFORMANCE THE DETERMINANTS OF PORTFOLIO PERFORMANCE THE BEHAVIORAL BIAS OF POSITIVE ECONOMICS THE SAMUELSON DICTUM REFERENCES NOTES

CHAPTER 4: Time Diversification

FALLACY: TIME DIVERSIFIES RISK SAMUELSON'S BET TIME, VOLATILITY, AND PROBABILITY OF LOSS TIME AND EXPECTED UTILITY WITHIN-HORIZON RISK A PREFERENCE-FREE CONTRADICTION TO TIME DIVERSIFICATION THE BOTTOM LINE REFERENCES NOTES

CHAPTER 5: Error Maximization

FALLACY: OPTIMIZED PORTFOLIOS ARE HYPERSENSITIVE TO INPUT ERRORS THE INTUITIVE ARGUMENT THE EMPIRICAL ARGUMENT THE ANALYTICAL ARGUMENT THE BOTTOM LINE REFERENCES NOTES

CHAPTER 6: Factors

FALLACY: FACTORS OFFER SUPERIOR DIVERSIFICATION AND NOISE REDUCTION WHAT IS A FACTOR? EQUIVALENCE OF ASSET CLASS AND FACTOR DIVERSIFICATION NOISE REDUCTION WHERE DOES THIS LEAVE US? REFERENCES NOTES

CHAPTER 7: 1/N

FALLACY: EQUALLY WEIGHTED PORTFOLIOS ARE SUPERIOR TO OPTIMIZED PORTFOLIOS THE CASE FOR 1/N SETTING THE RECORD STRAIGHT EMPIRICAL EVIDENCE IN DEFENSE OF OPTIMIZATION PRACTICAL PROBLEMS WITH 1/N BROKEN CLOCK THE BOTTOM LINE REFERENCES NOTE

SECTION Three: Challenges to Asset Allocation

CHAPTER 8: Necessary Conditions for Mean-Variance Analysis

THE CHALLENGE DEPARTURES FROM ELLIPTICAL DISTRIBUTIONS DEPARTURES FROM QUADRATIC UTILITY FULL-SCALE OPTIMIZATION THE CURSE OF DIMENSIONALITY APPLYING FULL-SCALE OPTIMIZATION SUMMARY REFERENCES NOTES

CHAPTER 9: Constraints

THE CHALLENGE WRONG AND ALONE MEAN-VARIANCE-TRACKING ERROR OPTIMIZATION REFERENCES NOTE

CHAPTER 10: Currency Risk

THE CHALLENGE WHY HEDGE? WHY NOT HEDGE EVERYTHING? LINEAR HEDGING STRATEGIES NONLINEAR HEDGING STRATEGIES ECONOMIC INTUITION REFERENCES NOTES

CHAPTER 11: Illiquidity

THE CHALLENGE SHADOW ASSETS AND LIABILITIES EXPECTED RETURN AND RISK OF SHADOW ALLOCATIONS OTHER CONSIDERATIONS CASE STUDY THE BOTTOM LINE APPENDIX REFERENCES NOTES

CHAPTER 12: Risk in the Real World

THE CHALLENGE END-OF-HORIZON EXPOSURE TO LOSS WITHIN-HORIZON EXPOSURE TO LOSS REGIMES THE BOTTOM LINE REFERENCES NOTES

CHAPTER 13: Estimation Error

THE CHALLENGE TRADITIONAL APPROACHES TO ESTIMATION ERROR STABILITY-ADJUSTED OPTIMIZATION BUILDING A STABILITY-ADJUSTED RETURN DISTRIBUTION DETERMINING THE OPTIMAL ALLOCATION EMPIRICAL ANALYSIS THE BOTTOM LINE REFERENCES NOTES

CHAPTER 14: Leverage versus Concentration

THE CHALLENGE LEVERAGE IN THEORY LEVERAGE IN PRACTICE THE BOTTOM LINE REFERENCES NOTES

CHAPTER 15: Rebalancing

THE CHALLENGE THE DYNAMIC PROGRAMMING SOLUTION THE MARKOWITZ–VAN DIJK HEURISTIC THE BOTTOM LINE REFERENCES NOTES

CHAPTER 16: Regime Shifts

THE CHALLENGE PREDICTABILITY OF RETURN AND RISK REGIME-SENSITIVE ALLOCATION TACTICAL ASSET ALLOCATION THE BOTTOM LINE APPENDIX: BAUM-WELCH ALGORITHM REFERENCES NOTES

SECTION Four: Addendum

CHAPTER 17: Key Takeaways CHAPTER 18: Statistical and Theoretical Concepts

DISCRETE AND CONTINUOUS RETURNS ARITHMETIC AND GEOMETRIC AVERAGE RETURNS STANDARD DEVIATION CORRELATION COVARIANCE COVARIANCE INVERTIBILITY MAXIMUM LIKELIHOOD ESTIMATION MAPPING HIGH-FREQUENCY STATISTICS ONTO LOW-FREQUENCY STATISTICS PORTFOLIOS PROBABILITY DISTRIBUTIONS THE CENTRAL LIMIT THEOREM THE NORMAL DISTRIBUTION HIGHER MOMENTS THE LOGNORMAL DISTRIBUTION ELLIPTICAL DISTRIBUTIONS PROBABILITY OF LOSS VALUE AT RISK UTILITY THEORY SAMPLE UTILITY FUNCTIONS ALTERNATIVE UTILITY FUNCTIONS EXPECTED UTILITY CERTAINTY EQUIVALENTS MEAN-VARIANCE ANALYSIS FOR MORE THAN TWO ASSETS EQUIVALENCE OF MEAN-VARIANCE ANALYSIS AND EXPECTED UTILITY MAXIMIZATION MONTE CARLO SIMULATION BOOTSTRAP SIMULATION REFERENCES NOTE

CHAPTER 19: Glossary of Terms

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