Asset Allocation: From Theory to Practice and Beyond
- Length: 368 pages
- Edition: 1
- Language: English
- Publisher: Wiley
- Publication Date: 2021-07-27
- ISBN-10: 1119817714
- ISBN-13: 9781119817710
- Sales Rank: #70538 (See Top 100 Books)
Discover a masterful exploration of the fallacies and challenges of asset allocation
In Asset Allocation: From Theory to Practice and Beyond―the newly and substantially revised Second Edition of A Practitioner’s Guide to Asset Allocation―accomplished finance professionals William Kinlaw, Mark P. Kritzman, and David Turkington deliver a robust and insightful exploration of the core tenets of asset allocation.
Drawing on their experience working with hundreds of the world’s largest and most sophisticated investors, the authors review foundational concepts, debunk fallacies, and address cutting-edge themes like factor investing and scenario analysis. The new edition also includes references to related topics at the end of each chapter and a summary of key takeaways to help readers rapidly locate material of interest.
The book also incorporates discussions of:
- The characteristics that define an asset class, including stability, investability, and similarity
- The fundamentals of asset allocation, including definitions of expected return, portfolio risk, and diversification
- Advanced topics like factor investing, asymmetric diversification, fat tails, long-term investing, and enhanced scenario analysis as well as tools to address challenges such as liquidity, rebalancing, constraints, and within-horizon risk.
Perfect for client-facing practitioners as well as scholars who seek to understand practical techniques, Asset Allocation: From Theory to Practice and Beyond is a must-read resource from an author team of distinguished finance experts and a forward by Nobel prize winner Harry Markowitz.
Cover Table of Contents Title Page Copyright Foreword to the First Edition Preface Key Takeaways Chapter 1: What Is an Asset Class? Chapter 2: Fundamentals of Asset Allocation Chapter 3: The Importance of Asset Allocation Chapter 4: Time Diversification Chapter 5: Divergence Chapter 6: Correlation Asymmetry Chapter 7: Error Maximization Chapter 8: Factors Chapter 9: 1/N Chapter 10: Policy Portfolios Chapter 11: The Private Equity Leverage Myth Chapter 12: Necessary Conditions for Mean‐Variance Analysis Chapter 13: Forecasting Chapter 14: The Stock–Bond Correlation Chapter 15: Constraints Chapter 16: Asset Allocation Versus Factor Investing Chapter 17: Illiquidity Chapter 18: Currency Risk Chapter 19: Estimation Error Chapter 20: Leverage Versus Concentration Chapter 21: Rebalancing Chapter 22: Regime Shifts Chapter 23: Scenario Analysis Chapter 24: Stress Testing CHAPTER 1: What Is an Asset Class? STABLE AGGREGATION 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 THE SHARPE ALGORITHM REFERENCES NOTES CHAPTER 3: The Importance of Asset Allocation FALLACY: ASSET ALLOCATION DETERMINES MORE THAN 90% OF PERFORMANCE THE DETERMINANTS OF PORTFOLIO PERFORMANCE THE BEHAVIORAL BIAS OF POSITIVE ECONOMICS THE SAMUELSON DICTUM THE BOTTOM LINE RELATED TOPICS 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 RELATED TOPICS REFERENCES NOTES CHAPTER 5: Divergence FALLACY: VOLATILITY SCALES WITH THE SQUARE ROOT OF TIME, AND CORRELATION IS CONSTANT ACROSS RETURN INTERVALS EXCESS DISPERSION THE EVIDENCE THE INTUITION THE MATH IMPLICATIONS THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 6: Correlation Asymmetry FALLACY: DIVERSIFICATION IS SYMMETRIC CORRELATION MATHEMATICS CORRELATION ASYMMETRY BETWEEN ASSET CLASSES IMPLICATIONS FOR PORTFOLIO CONSTRUCTION THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 7: Error Maximization FALLACY: OPTIMIZED PORTFOLIOS ARE HYPERSENSITIVE TO INPUT ERRORS THE INTUITIVE ARGUMENT THE EMPIRICAL ARGUMENT THE ANALYTICAL ARGUMENT THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 8: Factors FALLACY: FACTORS OFFER SUPERIOR DIVERSIFICATION AND NOISE REDUCTION WHAT IS A FACTOR? EQUIVALENCE OF ASSET CLASS AND FACTOR DIVERSIFICATION NOISE REDUCTION THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 9: 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 RELATED TOPICS REFERENCES NOTE CHAPTER 10: Policy Portfolios FALLACY: POLICY PORTFOLIOS MATTER RISK INSTABILITY WHAT INVESTORS WANT RESPONDING TO RISK REGIMES THE BOTTOM LINE RELATED TOPICS REFERENCE CHAPTER 11: The Private Equity Leverage Myth FALLACY: PRIVATE EQUITY VOLATILITY SCALES WITH ITS LEVERAGE THE PRIVATE EQUITY LEVERAGE PUZZLE LEVERAGE AND VOLATILITY IN THE PUBLIC EQUITY MARKET THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 12: 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 THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 13: Forecasting THE CHALLENGE CONVENTIONAL LINEAR REGRESSION REGRESSION REVISITED PARTIAL SAMPLE REGRESSION THE BOTTOM LINE RELATED TOPICS REFERENCES NOTE CHAPTER 14: The Stock–Bond Correlation THE CHALLENGE SINGLE‐PERIOD CORRELATION FUNDAMENTAL PREDICTORS OF THE STOCK–BOND CORRELATION MODEL SPECIFICATION MODEL RESULTS THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 15: Constraints THE CHALLENGE WRONG AND ALONE MEAN‐VARIANCE‐TRACKING ERROR OPTIMIZATION THE BOTTOM LINE REFERENCE NOTE CHAPTER 16: Asset Allocation Versus Factor Investing THE CHALLENGE PORTFOLIO CONSTRUCTION CASE STUDY THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 17: Illiquidity THE CHALLENGE SHADOW ASSETS AND LIABILITIES EXPECTED RETURN AND RISK OF SHADOW ALLOCATIONS OTHER CONSIDERATIONS CASE STUDY THE BOTTOM LINE RELATED TOPICS APPENDIX REFERENCES NOTES CHAPTER 18: Currency Risk THE CHALLENGE WHY HEDGE? WHY NOT HEDGE EVERYTHING? LINEAR HEDGING STRATEGIES NONLINEAR HEDGING STRATEGIES THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 19: 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 RELATED TOPICS REFERENCES NOTES CHAPTER 20: Leverage Versus Concentration THE CHALLENGE LEVERAGE IN THEORY LEVERAGE IN PRACTICE THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 21: Rebalancing THE CHALLENGE THE DYNAMIC PROGRAMMING SOLUTION THE MVD HEURISTIC THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 22: Regime Shifts THE CHALLENGE PREDICTABILITY OF RETURN AND RISK REGIME‐SENSITIVE ALLOCATION TACTICAL ASSET ALLOCATION THE BOTTOM LINE APPENDIX: BAUM–WELCH ALGORITHM RELATED TOPICS REFERENCES NOTES CHAPTER 23: Scenario Analysis THE CHALLENGE COMPARISON TO MEAN‐VARIANCE ANALYSIS THE MAHALANOBIS DISTANCE APPLIED TO SCENARIO ANALYSIS THE MAHALANOBIS DISTANCE AND PROBABILITY REVISING PROBABILITIES CASE STUDY MAPPING ECONOMIC VARIABLES ONTO ASSET CLASS RETURNS THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 24: Stress Testing THE CHALLENGE END‐OF‐HORIZON EXPOSURE TO LOSS WITHIN‐HORIZON EXPOSURE TO LOSS REGIMES THE BOTTOM LINE RELATED TOPICS REFERENCES NOTES CHAPTER 25: 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 THE MAHALANOBIS DISTANCE 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 NOTES Glossary of Terms Index End User License Agreement
Donate to keep this site alive
1. Disable the AdBlock plugin. Otherwise, you may not get any links.
2. Solve the CAPTCHA.
3. Click download link.
4. Lead to download server to download.