Quantitative Equity Portfolio Management_ An Active Approach to Portfolio Construction and Management

Cover
Title Page
Copyright Page
Contents
Foreword
Preface to the First Edition
Preface to the Second Edition
Notations and Abbreviations
I. An Overview of QEPM
	1. The Power of QEPM
		1.1 Introduction
		1.2 The Advantages of QEPM
		1.3 Quantitative and Qualitative Approaches to Similar Investment Situations
		1.4 A Tour of the Book
		1.5 Conclusion
	2. The Fundamentals of QEPM
		2.1 Introduction
		2.2 QEPM α
		2.2.1 Benchmark α
			2.2.2 CAPM α
			2.2.3 Multifactor α
			2.2.4 A Variety of α’s
			2.2.5 Ex-Ante and Ex-Post α
			2.2.6 Ex-Ante and Ex-Post Information Ratio
		2.3 The Seven Tenets of QEPM
		2.4 Tenets 1 and 2: Market Efficiency and Qepm
			2.4.1 The Efficient-Market Hypothesis
			2.4.2 Anomalies
			2.4.3 Market Efficiency and QEPM
		2.5 Tenets 3 and 4: The Fundamental Law, the Information Criterion, and Qepm
			2.5.1 The Truth about the Fundamental Law
			2.5.2 The Information Criterion
			2.5.3 Information Loss
		2.6 Tenets 5, 6, and 7: Statistical Issues in QEPM
			2.6.1 Data Mining
			2.6.2 Parameter Stability
			2.6.3 Parameter Uncertainty
		2.7 Conclusion
	3. Basic QEPM Models
		3.1 Introduction
		3.2 Basic QEPM Models and Portfolio Construction Procedures
			3.2.1 Factor Choice
			3.2.2 The Data Decision
			3.2.3 Factor Exposure
			3.2.4 Factor Premium
			3.2.5 Expected Return
			3.2.6 Risk
			3.2.7 Forecasting
			3.2.8 Security Weighting
		3.3 The Equivalence of the Basic Models
		3.4 The Screening and Ranking of Stocks with the Z-Score
		3.5 Hybrids of the Models and the Information Criterion
			3.5.1 The Setup
			3.5.2 The Z-Score Model
			3.5.3 A Hybrid of the Z-Score Model and a Fundamental Factor Model
			3.5.4 Information Loss
		3.6 Choosing the Right Model
			3.6.1 Consistency with Economic Theory
			3.6.2 Ability to Combine Different Types of Factors
			3.6.3 Ease of Implementation
			3.6.4 Data Requirement
			3.6.5 Intuitive Appeal
		3.7 Conclusion
II. Portfolio Construction and Maintenance
	4. Factors and Factor Choice
		4.1 Introduction
		4.2 Fundamental Factors
			4.2.1 Valuation Factors
			4.2.2 Size Factors
			4.2.3 Operating Efficiency Factors
			4.2.4 Operating Profitability Factors
			4.2.5 Solvency Factors
			4.4.6 Financial Risk Factors
			4.2.7 Corporate Activity Factors
		4.3 Technical Factors
			4.3.1 Liquidity Risk Factors
			4.3.2 Price-Based Factors
			4.3.3 Volume-Based Factors
			4.3.4 Overall Market Movement Factors
		4.4 Economic Factors
		4.5 Alternative Factors
			4.5.1 Analyst Factors
			4.5.2 Captivus Factors
			4.5.3 Social Responsibility Factors
		4.6 Factor Choice
			4.6.1 Univariate Regression Tests
			4.6.2 Multiple Regression Tests
			4.6.3 Unidimensional Zero-Investment Portfolio
			4.6.4 Multidimensional Zero-Investment Portfolio
			4.6.5 Techniques to Reduce the Number of Factors
		4.7 Conclusion
	Appendix 4A: Factor Definition Tables
	Appendix 4B: On Data Mining and Techniques to Adjust the Significance of Factors
		4B.1 The Bonferroni-Type Adjustment
		4B.2 A Bayesian Adjustment
	5. Stock Screening and Ranking
		5.1 Introduction
		5.2 Sequential Stock Screening
		5.3 Sequential Screens Based on Famous Strategies
		5.4 Simultaneous Screening and the Aggregate Z-Score
			5.4.1 The Z-Score
			5.4.2 The Aggregate Z-Score
			5.4.3 Ad Hoc Aggregate Z-Score
			5.4.4 Optimal Aggregate Z-Score
			5.4.5 Factor Groups and the Aggregate Z-Score
		5.5 The Aggregate Z-Score and Expected Return
			5.5.1 Expected Return Implied by the Z-Score
			5.5.2 Forecasting Rule of Thumb
			5.5.3 The Equivalence between the Z-Score Model and the Fundamental Factor Model
		5.6 The Aggregate Z-Score and the Multifactor α
		5.7 Conclusion
	Appendix 5A: A List of Stock Screens Based on Well-Known Strategies
	Appendix 5B: On Outliers
		5B.1 General Concepts
		5B.2 Specific Practical Techniques
			5B.2.1 Utilizing the Z-Score
			5B.2.2 The Interquartile Method
			5B.2.3 The Ranking Method
			5B.2.4 The Percentile Ranking Method
	Appendix 5C: Converting Z-Scores to Returns
		5C.1 A Numerical Example
	6. Fundamental Factor Models
		6.1 Introduction
		6.2 Preliminary Work
			6.2.1 Choosing Factors
			6.2.2 Treatment of the Risk-Free Rate
			6.2.3 Choosing the Time Interval and Time Period
			6.2.4 Choosing the Universe of Stocks
		6.3 Benchmark and α
		6.4 Factor Exposure
		6.5 The Factor Premium
			6.5.1 OLS Estimator of the Factor Premium
			6.5.2 Robustness Check
			6.5.3 Outliers and MAD Estimator of Factor Premium
			6.5.4 Heteroscedasticity- and Autocorrelation-Consistent Estimation of the Standard Error
		6.6 Decomposition of Risk
		6.7 Conclusion
	7. Economic Factor Models
		7.1 Introduction
		7.2 Preliminary Work
		7.3 Benchmark and α
		7.4 The Factor Premium
			7.4.1 Factor Premium for Economic/Behavioral/Market Factors
			7.4.2 Factor Premium for Fundamental/Technical/Analyst Factors
			7.4.3 Factor Premium for Statistical Factors
		7.5 Factor Exposure
			7.5.1 The Standard Approach
			7.5.2 When the Standard Approach Fails
		7.6 Decomposition of Risk
			7.6.1 The Standard Approach
			7.6.2 When the Standard Approach Fails
		7.7 Conclusion
	8. Forecasting Factor Premiums and Exposures
		8.1 Introduction
		8.2 When Is Forecasting Necessary?
		8.3 Combining External Forecasts
		8.4 Model-Based Forecast
		8.5 Econometric Forecast
		8.6 Parameter Uncertainty
		8.7 Forecasting the Stock Return
		8.8 Conclusion
	9. Portfolio Weights
		9.1 Introduction
		9.2 Ad Hoc Methods
		9.3 Standard Mean-Variance Optimization
			9.3.1 No Constraints
			9.3.2 Short-Sale and Diversification Constraints
			9.3.3 Sector or Industry Constraints
			9.3.4 Trading-Volume Constraint
			9.3.5 Risk-Adjusted Return
		9.4 Benchmark
		9.5 Ad Hoc Methods Again
		9.6 Stratification
		9.7 Factor Exposure Targeting
		9.8 Tracking-Error Minimization
			9.8.1 Direct Computation
			9.8.2 Tracking by Factor Exposure
			9.8.3 Ghost Benchmark Tracking
			9.8.4 Risk-Adjusted Tracking Error
		9.9 Conclusion
	Appendix 9A: Quadratic Programming
		9A.1 Quadratic Programming with Equality Constraints
			9A.1.1 A Numerical Example
		9A.2 Quadratic Programming With Inequality Constraints
			9A.2.1 A Numerical Example
	Appendix 9B: Advanced Techniques for Quadratic Optimization
		9B.1 Phantom Weights
		9B.2 Binary Weights
		9B.3 Quadratic Constraints
		9B.4 Practical Examples
			9B.4.1 Market Neutrality with Leverage Constraints
			9B.4.2 Transactions Costs
			9B.4.3 Elimination of Small-Weight Stocks
			9B.4.4 Restricting the Number of Stocks
	10. Rebalancing and Transactions Costs
		10.1 Introduction
		10.2 The Rebalancing Decision
			10.2.1 Rebalancing and Model Periodicity
			10.2.2 Change in α and Other Parameters
		10.3 Understanding Transactions Costs
		10.4 Modeling Transactions Costs
		10.5 Portfolio Construction With Transactions Costs
			10.5.1 The Optimal Portfolio with Transactions Costs
			10.5.2 The Tracking Portfolio with Transactions Costs
		10.6 Dealing with Cash Flows
			10.6.1 Reducing Transactions Costs Using Futures and ETFs
			10.6.2 Rebalancing toward Optimal Target Weights
		10.7 Conclusion
	Appendix 10A: Approximate Solution to the Optimal Portfolio Problem
	Appendix 10B: An Exact Solution to the Optimal Portfolio Problem
		10B.1 A Numerical Example
	Appendix 10C: An Approximate Optimal Portfolio with Market Impact Costs
	10C.1 Approximation of Transactions Costs
	10C.2 Long-Only Portfolio
	10C.3 Market-Neutral Portfolio
	10C.4 Market Impact during Rebalancing
	10C.5 A Numerical Example
	11. Tax Management
		11.1 Introduction
		11.2 Dividends, Capital Gains, and Capital Losses
		11.3 Principles of Tax Management
		11.4 Dividend Management
		11.5 Tax-Lot Management
		11.6 Tax-Lot Mathematics
		11.7 Capital Gain and Loss Management
		11.8 Loss Harvesting
			11.8.1 Loss Harvesting and Reoptimizing
			11.8.2 Loss Harvesting and Characteristic Matching
			11.8.3 Loss Harvesting with a Benchmark
		11.9 Gains from Tax Management
		11.10 Conclusion
III. α Mojo
	12. Leverage
		12.1 Introduction
		12.2 Cash and Index Futures
			12.2.1 Theoretical Limits of Leverage
			12.2.2 Leverage Mechanics
			12.2.3 Expected Return and Risk
		12.3 Stocks, Cash, and Index Futures
			12.3.1 Theoretical Limits to Leverage
			12.3.2 Leverage Mechanics
			12.3.3 Expected Returns and Risk
		12.4 Stocks, Cash, and Single-Stock Futures
			12.4.1 Theoretical Limits of Leverage
			12.4.2 Leverage Mechanics
			12.4.3 Expected Returns, Risk, and α Mojo
		12.5 Stocks, Cash, Individual Stocks, and Single-Stock and Basket Swaps
			12.5.1 Margining Individual Stocks
			12.5.2 Single-Stock and Basket Swaps
		12.6 Stocks, Cash, and Options
		12.7 Rebalancing
			12.7.1 Cash and Futures
			12.7.2 Stocks, Cash, and Futures
		12.8 Liquidity Buffering
		12.9 Leveraged Short
		12.10 Conclusion
	Appendix 12A: Fair-Value Computations
	Appendix 12B: Derivation of Equations (12.21), (12.22), and (12.23)
	Appendix 12C: Tables of Futures Leverage Multipliers Needed to Achieve Various Degrees of Leverage
	13. Market Neutral
		13.1 Introduction
		13.2 Market-Neutral Construction
			13.2.1 Security Selection
			13.2.2 Dollar Neutrality
			13.2.3 Beta Neutrality (a.k.a. Risk-Factor Neutrality)
			13.2.4 Market-Neutral Portfolio Out of a Long-Only Portfolio
		13.3 Market Neutral’s Mojo
		13.4 The Mechanics of Market Neutral
			13.4.1 Margin and Shorting
			13.4.2 The Margin and Market Neutral
			13.4.3 Sources of the Return
		13.5 The Benefits and Drawbacks of Market Neutral
		13.6 Rebalancing
		13.7 General Long-Short
			13.7.1 Long-Short
			13.7.2 Equitization
			13.7.3 Portable α
			13.7.4 Pair Trading
		13.8 Conclusion
	Appendix 13A: Market-Neutral Portfolio Construction Techniques
		13A.1 A Numerical Example
	14. Bayesian α
		14.1 Introduction
		14.2 The Basics of Bayesian Theory
		14.3 Bayesian α Mojo
		14.4 Quantifying Qualitative Information
			14.4.1 Quantifying a Stock Screen
			14.4.2 Quantifying a Stock Ranking
			14.4.3 Quantifying the Buy and Sell Recommendations
		14.5 The Z-Score-Based Prior
		14.6 Scenario-Based Priors
		14.7 Posterior Computation
		14.8 The Information Criterion and Bayesian α
		14.9 Conclusion
IV. Performance Analysis
	15. Performance Measurement and Attribution
		15.1 Introduction
		15.2 Measuring Returns
			15.2.1 No Cash Flows
			15.2.2 Inflows and Outflows
			15.2.3 Measuring Returns for Market-Neutral and Leveraged Portfolios
		15.3 Measuring Risk
			15.3.1 Standard Deviation
			15.3.2 Semi–Standard Deviation
			15.3.3 Tracking Error
			15.3.4 CAPM β
			15.3.5 Value-at-Risk
			15.3.6 Covariance and Correlation
		15.4 Risk-Adjusted Performance Measurement
			15.4.1 The Sharpe Ratio
			15.4.2 The Information Ratio
			15.4.3 The CAPM α and the Benchmark α
			15.4.4 The Multifactor α
			15.4.5 Practical Issues with Risk-Adjusted Measures
		15.5 Performance Attribution
			15.5.1 Classical Attribution
			15.5.2 Multifactor QEPM Attribution
		15.6 Conclusion
	Appendix 15A: Style Analysis
	Appendix 15B: Measures of Opportunity
	Appendix 15C: Short Returns
		15C.1 A Numerical Example
	Appendix 15D: Measuring Market Timing Ability
V. Practical Application
	16. The Backtesting Process
		16.1 Introduction
		16.2 The Data and Software
		16.3 The Time Period
		16.4 The Investment Universe and the Benchmark
			16.4.1 U.S. Equity Benchmarks
			16.4.2 A Comparison of the Major U.S. Equity Benchmarks
			16.4.3 The Most Popular Benchmarks and Our Benchmarks
		16.5 The Factors
		16.6 The Stock Return and Risk Models
		16.7 Parameter Stability and the Rebalancing Frequency
		16.8 The Various Types of Constructed Portfolios
			16.8.1 Transaction Costs
			16.8.2 Taxes
			16.8.3 Leverage
			16.8.4 Market-Neutral
		16.9 Conclusion
	Appendix 16A: Factor Formulas
	17. The Portfolios’ Performance
		17.1 Introduction
		17.2 The Performance of the Baseline Portfolio and Variations
			17.2.1 The Fundamental Factor Model Performance
			17.2.2 The Aggregate Z-Score Model Performance
			17.2.3 The Economic Factor Model Performance
			17.2.4 Performance Reports for Distribution
			17.2.5 Performance Attribution for the Fundamental Factor Model Baseline Portfolio
		17.3 The Transactions Cost–Managed Portfolio Performance
		17.4 The Tax-Managed Portfolio Performance
		17.5 The Leveraged Portfolio Performance
		17.6 The Market-Neutral Portfolio Performance
		17.7 Conclusion
Glossary
Bibliography
About the Authors
Index