Bruce I Jacobs, Kenneth N Levy

Equity Management: The Art and Science of Modern Quantitative Investing, Second Edition

• Gebundenes Buch

Produktbeschreibung

The classic guide to quantitative investing-expanded and updated for today's increasingly complex markets From Bruce Jacobs and Ken Levy-two pioneers of quantitative equity management- the go-to guide to stock selection has been substantially updated to help you build portfolios in today's transformed investing landscape. A powerful combination of in-depth research and expert insights gained from decades of experience, Equity Management, Second Edition includes 24 new peer-reviewed articles that help leveraged long-short investors and leverage-averse investors navigate today's complex and unpredictable markets. Retaining all the content that made an instant classic of the first edition-including the authors' innovative approach to disentangling the many factors that influence stock returns, unifying the investment process, and integrating long and short portfolio positions-this new edition addresses critical issues. Among them-- . What's the best leverage level for long-short and leveraged long-only portfolios? . Which behavioral characteristics explain the recent financial meltdown and previous crises? . What is smart beta-and why should you think twice about using it? . How do option-pricing theory and arbitrage strategies lead to market instability? . Why are factor-based strategies on the rise? Equity Management provides the most comprehensive treatment of the subject to date. More than a mere compilation of articles, this collection provides a carefully structured view of modern quantitative investing. You'll come away with levels of insight and understanding that will give you an edge in increasingly complex and unpredictable markets. Well-established as two of today's most innovative thinkers, Jacobs and Levy take you to the next level of investing. Read Equity Management and design the perfect portfolio for your investing goals.

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Produktdetails

• Verlag: McGraw Hill LLC
• 2nd edition
• Seitenzahl: 896
• Erscheinungstermin: 12. Dezember 2016
• Englisch
• Abmessung: 236mm x 156mm x 71mm
• Gewicht: 1232g
• ISBN-13: 9781259835247
• ISBN-10: 1259835243
• Artikelnr.: 45161907

Autorenporträt

Bruce I. Jacobs holds a Ph.D. in finance from the Wharton School of the University of Pennsylvania. He is the author of Too Smart for Our Own Good: Ingenious Investment Strategies, Illusions of Safety, and Market Crashes, and Capital Ideas and Market Realities: Option Replication, Investor Behavior, and Stock Market Crashes, and co-editor, with Ken Levy, of Market Neutral Strategies. He serves on the advisory board of the Journal of Portfolio Management.

Inhaltsangabe

Foreword to First Edition by Harry M. Markowitz, Nobel Laureate
Foreword to Second Edition by Harry M. Markowitz, Nobel Laureate
Preface
Acknowledgments
INTRODUCTION Our Approach to Quantitative Investing
PART ONE Profiting in a Multidimensional, Dynamic World
Chapter 1 Ten Investment Insights that Matter The Stock Market Is a Complex
System Market Complexity Can be Exploited with a Rich, Multidimensional
Model Return-Predictor Relationships Should Be Disentangled An Investment
Firm Should Abide By the Law of One Alpha The Investment Process Should Be
Dynamic and Transparent A Customized, Integrated Investment Process
Preserves Insights Integrated Long-Short Optimization Can Provide Enhanced
Returns and Risk Control for Market-Neutral and 130-30 Portfolios Alpha
from Security Selection Can Be Transported to Any Asset Class Portfolio
Optimization Should Take into Account an Investor's Aversion to Leverage
Beware of Risk Shifting, Free Lunches, and Irrational Markets Conclusion
Chapter 2 The Complexity of the Stock Market The Evolution of Investment
Practice Web of Return Regularities Disentangling and Purifying Returns
Advantages of Disentangling Evidence of Inefficiency Value Modeling in an
Inefficient Market Risk Modeling versus Return Modeling Pure Return Effects
Anomalous Pockets of Inefficiency Empirical Return Regularities Modeling
Empirical Return Regularities Bayesian Random Walk Forecasting Conclusion
Chapter 3 Disentangling Equity Return Regularities: New Insights and
Investment Opportunities Previous Research Return Regularities We Consider
Methodology The Results on Return Regularities P/E and Size Effects Yield,
Neglect, Price, and Risk Trends and Reversals Some Implications January
versus Rest-of-Year Returns Autocorrelation of Return Regularities Return
Regularities and Their Macroeconomic Linkages Conclusion
Chapter 4 On the Value of 'Value' Value and Equity Attributes Market
Psychology, Value, and Equity Attributes The Importance of Equity
Attributes Examining the DDM Methodology Stability of Equity Attributes
Expected Returns Naïve Expected Returns Pure Expected Returns Actual
Returns Power of the DDM Power of Equity Attributes Forecasting DDM Returns
Conclusion
Chapter 5 Calendar Anomalies: Abnormal Returns at Calendar Turning Points
The January Effect Rationales The Turn-of-the-Month Effect The
Day-of-the-Week Effect Rationales The Holiday Effect The Time-of-Day Effect
Conclusion
Chapter 6 Forecasting the Size Effect The Size Effect Size and Transaction
Costs Size and Risk Measurement Size and Risk Premiums Size and Other
Cross-Sectional Effects Size and Calendar Effects Modeling the Size Effect
Simple Extrapolation Techniques Time-Series Techniques Transfer Functions
Vector Time-Series Models Structural Macroeconomic Models Bayesian Vector
Time-Series Models
Chapter 7 Earnings Estimates, Predictor Specification, and Measurement
Error Predictor Specification and Measurement Error Alternative
Specifications of E/P and Earnings Trend for Screening Alternative
Specifications of E/P and Trend for Modeling Returns Predictor
Specification with Missing Values Predictor Specification and Analyst
Coverage The Return-Predictor Relationship and Analyst Coverage Summary
PART TWO Managing Portfolios in a Multidimensional, Dynamic World
Chapter 8 Engineering Portfolios: A Unified Approach Is the Market
Segmented or Unified? A Unified Model A Common Evaluation Framework
Portfolio Construction and Evaluation Engineering 'Benchmark' Strategies
Added Flexibility Economies
Chapter 9 The Law of One Alpha
Chapter 10 Residual Risk: How Much Is Too Much? Beyond the Curtain Some
Implications
Chapter 11 High-Definition Style Rotation High-Definition Style Pure Style
Returns Implications High-Definition Management Benefits of High-Definition
Style
Chapter 12 Smart Beta versus Smart Alpha Supported By Theory? Active or
Passive? Forward-Looking and Dynamic? Concentrated Risk Exposures?
Unintended Risk Exposures? Factor Integration and Risk Control? Turnover
Levels? Liquidity and Overcrowding? Transparent or Proprietary? Conclusion
Chapter 13 Smart Beta: Too Good To Be True? Smart Beta Portfolios are
Passive Smart Beta Targets the Most Significant Return-Generating Factors
Smart Beta Portfolios are Well Diversified Smart Beta Factors Perform
Consistently Smart Beta Portfolios Benefit from Mean-Reversion in Prices
Smart Beta Portfolios Can be Efficiently Combined Smart Beta Benefits from
Transparency Smart Beta has Nearly Unlimited Capacity Smart Beta
Streamlines the Investment Decision Process for Investors Smart Beta Costs
Less than Active Investing Conclusion
Chapter 14 Is Smart Beta State of the Art?
Chapter 15 Investing in a Multidimensional Market The Market's
Multidimensionality Advantages of a Multidimensional Approach Conclusion
PART THREE Expanding Opportunities with Market-Neutral Long-Short
Portfolios
Chapter 16 Long-Short Equity Investing Long-Short Equity Strategies
Societal Advantages of Short-Selling Equilibrium Models, Short-Selling, and
Security Prices Practical Benefits of Long-Short Investing Portfolio Payoff
Patterns Long-Short Mechanics and Returns Theoretical Tracking Error
Advantages of the Market-Neutral Strategy over Long Manager plus Short
Manager Advantages of the Equitized Strategy over Traditional Long Equity
Management Implementation of Long-Short Strategies: Quantitative versus
Judgmental Implementation of Long-Short Strategies: Portfolio Construction
Alternatives Practical Issues and Concerns Shorting Issues Trading Issues
Custody Issues Legal Issues Morality Issues What Asset Class Is Long-Short?
Conclusion
Chapter 17 20 Myths About Long-Short
Chapter 18 The Long and Short on Long-Short Building a Market-Neutral
Portfolio A Question of Efficiency Benefits of Long-Short Equitizing
Long-Short Trading Long-Short Evaluating Long-Short
Chapter 19 Long-Short Portfolio Management: An Integrated Approach
Long-Short: Benefits and Costs The Real Benefits of Long-Short Costs:
Perception versus Reality The Optimal Portfolio Neutral Portfolios Optimal
Equitization Conclusion
Chapter 20 Alpha Transport with Derivatives Asset Allocation or Security
Selection Asset Allocation and Security Selection Transporter Malfunctions
Matter-Antimatter Warp Drive To Boldly Go
PART FOUR Expanding Opportunities with Enhanced Active 130-30 Portfolios
Chapter 21 Enhanced Active Equity Strategies: Relaxing the Long-Only
Constraint in the Pursuit of Active Return Approaches to Equity Management
Enhanced Active Equity Portfolios Performance: An Illustration The Enhanced
Prime Brokerage Structure Operational Considerations Comparison to Other
Long-Short Strategies Conclusion Appendix: Weighted-Average Capitalization
Weights
Chapter 22 20 Myths About Enhanced Active 120-20 Strategies
Chapter 23 Enhanced Active Equity Portfolios Are Trim Equitized Long-Short
Portfolios Market-Neutral, Equitized, and Enhanced Active Portfolios
Trimming an Equitized Portfolio Enhanced Active versus Equitized Portfolios
Benchmark Index Choices Conclusion
Chapter 24 On the Optimality of Long-Short Strategies Portfolio
Construction and Problem Formulation Optimal Long-Short Portfolios
Optimality of Dollar Neutrality Optimality of Beta Ne utrality Optimal
Long-Short Portfolio with Minimum Residual Risk Optimal Long-Short
Portfolio with Specified Residual Risk Optimal Equitized Long-Short
Portfolio Optimality of Dollar Neutrality with Equitization Optimality of
Beta Neutrality with Equitization Optimal Equitized Long-Short Portfolio
with Specified Residual Risk Optimal Equitized Long-Short Portfolio with
Constrained Beta Conclusion
PART FIVE Optimizing Portfolios with Short Positions
Chapter 25 Trimability and Fast Optimization of Long-Short Portfolios
General Mean-Variance Problem Long-Short Constraints in Practice
Diagonalized Models of Covariance Factor Models Scenario Models Historical
Covariance Models Modeling Long-Short Portfolios Applying Fast Techniques
to the Long-Short Model Trimability Consequences of Trimability Example
Summary
Chapter 26 Portfolio Optimization with Factors, Scenarios, and Realistic
Short Positions The General Mean-Variance Problem Solution to the General
Problem Diagonalizable Models of Covariance Factor Models Scenario Models
Historical Covariance Matrices Short Sales in Practice Modeling Short Sales
Solution to Long-Short Model Example Summary
PART SIX Optimizing Portfolios for Leverage-Averse Investors
Chapter 27 Leverage Aversion and Portfolio Optimality Optimal Enhancement
with Leverage Aversion An Example with Leverage Aversion Conclusion
Chapter 28 Leverage Aversion, Efficient Frontiers, and the Efficient Region
Specifying the Leverage-Aversion Term Specification of the
Leverage-Aversion Term Using Portfolio Total Volatility Optimal Portfolios
with Leverage-Aversion Based on Portfolio Total Volatility Efficient
Frontiers With and Without Leverage Aversion Efficient Frontiers for
Various Leverage-Tolerance Cases The Efficient Region Conclusion Appendix:
Comparison of the Enhancement Surfaces Using Two Different Specifications
Chapter 29 Introducing Leverage Aversion into Portfolio Theory and Practice
Chapter 30 A Comparison of the Mean-Variance-Leverage Optimization Model
and the Markowitz General Mean-Variance Portfolio Selection Model Leverage
Risk-A Third Dimension Quartic versus Quadratic Optimization Practical
Insights from the MVL Optimization Model Conclusion
Chapter 31 Traditional Optimization is Not Optimal for Leverage-Averse
Investors Mean-Variance Optimization with a Leverage Constraint The
Leverage-Averse Investor's Utility of Optimal Mean-Variance Portfolios
Mean-Variance-Leverage Optimization versus Leverage-Constrained
Mean-Variance Optimization Conclusion
Chapter 32 The Unique Risks of Portfolio Leverage: Why Modern Portfolio
Theory Fails and How to Fix It The Limitations of Mean-Variance
Optimization Mean-Variance Optimization with Leverage Constraints
Mean-Variance-Leverage Optimization Optimal Mean-Variance-Leverage
Portfolios and Efficient Frontiers The Mean-Variance-Leverage Efficient
Region The Mean-Variance-Leverage Efficient Surface Optimal
Mean-Variance-Leverage Portfolios versus Optimal Mean-Variance Portfolios
Volatility and Leverage in Real-Life Situations Conclusion
PART SEVEN Shifting Risk Can Lead to Financial Crises
Chapter 33 Option Pricing Theory and its Unintended Consequences
Chapter 34 When Seemingly Infallible Arbitrage Strategies Fail
Chapter 35 Momentum Trading: The New Alchemy
Chapter 36 Risk Avoidance and Market Fragility Insuring Specific versus
Systematic Risk Insurance and Systemic Risk Risk Sharing versus Risk
Shifting
Chapter 37 Tumbling Tower of Babel: Subprime Securitization and the Credit
Crisis Risk-Shifting Building Blocks RMBSs ABCP, SIVs, and CDOs CDSs What
Goes Up... The Rise of Subprime Low Risk for Sellers and Buyers High Risk
for the System ...Must Come Down Positive Feedback's Negative Consequences
Fault Lines Conclusion: Building From the Ruins
PART EIGHT Simulating Security Markets
Chapter 38 Financial Market Simulation Types of Dynamic Models JLM
Simulator Status Events Initialization Reoptimization Order Review End of
Day Objectives and Extensions Alternative Investor and Trader Behaviors
Model Size Advantages of Asynchronous Finance Models Caveat Conclusion
Chapter 39 Simulating Security Markets in Dynamic and Equilibrium Modes
Simulation Overview Dynamic Analysis Different Initial Random Seeds
Different Ratios of Momentum to Value Investors Trading and Anchoring Rules
Trading rules Anchoring rules Capital Market Equilibrium Expected Return
Estimation Method Case Study Conclusion
Index