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Quantitative equity portfolio management: an active approach to portfolio construction and management

Author: Chincarini, Ludwig B. ; Kim, DaehwanPublisher: McGraw-Hill, 2006.Language: EnglishDescription: 658 p. : Graphs ; 24 cm. includes CD-ROM / DVDISBN: 9780071459402Type of document: BookNote: CD available inside back coverBibliography/Index: Includes bibliographical references and index and glossary
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Item type Current location Collection Call number Status Notes Date due Barcode Item holds
Book Europe Campus
Main Collection
Print HG4529.5 .C45 2006
(Browse shelf)
001232051
Available CD available inside back cover 001232051
Total holds: 0

CD available inside back cover

Includes bibliographical references and index and glossary

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Quantitative Equity Portfolio Management An Active Approach to Portfolio Construction and Management Contents Foreword xv Preface xvii Notations and Abbreviations xxi I An Overview of QEPM 1 1 The Power of QEPM 3 1.1 Introduction 3 1.2 The Advantages of QEPM 7 1.3 Quantitative and Qualitative Approaches to Similar Investment Situations 12 1.4 A Tour of the Book 17 1.5 Conclusion 19 2 The Fundamentals of QEPM 21 2.1 Introduction 21 2.2 QEPM a 22 2.2.1 Benchmark a 23 2. 2.2 CAPM x 23 2.2.3 Multifactor x 24 2.2.4 A Variety of x's 24 2.2.5 Ex-Ante and Ex-Post a 26 2.2.6 Ex-Ante and Ex-Post Information Ratio 26 2.3 The Seven Tenets of QEPM 27 2.4 Tenets 1 and 2: Market Efficiency and QEPM 29 2.4.1 The Efficient-Market Hypothesis 29 2.4.2 Anomalies 33 2.4.3 Market Efficiency and QEPM 42 2.5 Tenets 3 and 4: The Fundamental Law, The Information Criterion, and QEPM 48 2.5.1 The Truth about the Fundamental Law 49 2.5.2 The Information Criterion 51 2.5.3 Information Loss 52 2.6 Tenets 5, 6, and 7: Statistical Issues in QEPM 52 2.6.1 Data Mining 53 2.6.2 Parameter Stability 57 2.6.3 Parameter Uncertainty 57 2.7 Conclusion 58 3 Basic QEPM Models 65 3.1 Introduction 65 3.2 Basic QEPM Models and Portfolio Construction Procedures 66 3.2.1 Factor Choice 67 3.2.2 The Data Decision 68 3.2.3 Factor Exposure 69 3.2.4 Factor Premium 70 3.2.5 Expected Return 71 3.2.6 Risk 71 3.2.7 Forecasting 72 3.2.8 Security Weighting 72 3.3 The Equivalence of the Basic Models 73 3.4 The Screening and Ranking of Stocks with the Z-Score 75 3.5 Hybrids of the Models and the Information Criterion 75 3.5.1 The Setup 76 3.5.2 The Z-Score Model 77 3.5.3 A Hybrid of the Z-Score Model and a Fundamental Factor Model 78 3.5.4 Information Loss 79 3.6 Choosing the Right Model 81 3.6.1 Consistency with Economic Theory 81 3.6.2 Ability to Combine Different Types of Factors 82 3.6.3 Ease of Implementation 82 3.6.4 Data Requirement 82 3.6.5 Intuitive Appeal 83 3.7 Conclusion 84 II Portfolio Construction and Maintenance 89 4. Factors and Factor Choice 91 4.1 Introduction 91 4.2 Fundamental Factors 92 4.2.1 Valuation Factors 92 4.2.2 Solvency Factors 97 4.2.3 Operating Efficiency Factors 99 4.2.4 Operating Profitability Factors 100 4.2.5 Financial Risk Factors 103 4.2.6 Liquidity Factors 104 4.3 Technical Factors 106 4.4 Economic Factors 107 4.5 Alternative Factors 108 4.5.1 Analyst Factors 108 4.5.2 Corporate Finance Policy Factors 110 4.5.3 Social Responsibility Factors 110 4.6 Factor Choice 111 4.6.1 Univariate Regression Tests 112 4.6.2 Multiple Regression Tests 113 4.6.3 Unidimensional Zero-Investment Portfolio 114 4.6.4 Multidimensional Zero-Investment Portfolio 116 4.6.5 Techniques to Reduce the Number of Factors 116 4.7 Conclusion 118 Appendix 4A: Factor Definition Tables 119 5. Stock Screening and Ranking 135 5.1 Introduction 135 5.2 Sequential Stock Screening 136 5.3 Sequential Screens Based on Famous Strategies 137 5.4 Simultaneous Screening and the Aggregate Z-Score 145 5.4.1 The Z-Score 147 5.4.2 The Aggregate Z-Score 149 5.4.3 Ad Hoc Aggregate Z-Score 150 5.4.4 Optimal Aggregate Z-Score 150 5.4.5 Factor Groups and the Aggregate Z-Score 154 5.5 The Aggregate Z-Score and Expected Return 158 5.5.1 Expected Return Implied by the Z-Score 158 5.5.2 The Forecasting Rule of Thumb 161 5.5.3 The Equivalence between the Z-Score Model and the Fundamental Factor Model 162 5.6 The Aggregate Z-Score and the Multifactor x 163 5.7 Conclusion 164 Appendix 5A: A List of Stock Screens Based on Well-Known Strategies 166 Appendix 5B: On Outliers 179 6. Fundamental Factor Models 185 6.1 Introduction 185 6.2 Preliminary Work 188 6.2.1 Choosing Factors 189 6.2.2 Treatment of the Risk-Free Rate 189 6.2.3 Choosing the Time Interval and Time Period 190 6.2.4 Choosing the Universe of Stocks 192 6.3 Benchmark and x 193 6.4 Factor Exposure 194 6.5 The Factor Premium 196 6.5.1 OLS Estimator of the Factor Premium 197 6.5.2 Robustness Check 199 6.5.3 Outliers and MAD Estimator of Factor Premium 200 6.5.4 Heteroscedasticity and GLS Estimator of the Factor Premium 201 6.6 Decomposition of Risk 202 6.7 Conclusion 205 7 Economic Factor Models 211 7.1 Introduction 211 7.2 Preliminary Work 214 7.3 Benchmark and a 216 7.4 The Factor Premium 217 7.4.1 Factor Premium for Economic/Behavioral/ Market Factors 218 7.4.2 Factor Premium for Fundamental/Technical/ Analyst Factors 219 7.4.3 Factor Premium for Statistical Factors 222 5 Factor Exposure 223 7.5.1 The Standard Approach 223 7.5.2 When the Standard Approach Fails 225 7.6 Decomposition of Risk 226 7.6.1 The Standard Approach 226 7.6.2 When the Standard Approach Fails 228 7.7 Conclusion 229 8 Forecasting Factor Premiums and Exposures 235 8.1 Introduction 235 8.2 When Is Forecasting Necessary? 236 8.3 Combining External Forecasts 237 8.4 Model-Based Forecast 238 8.5 Econometric Forecast 239 8.6 Parameter Uncertainty 242 8.7 Forecasting the Stock Return 244 8.8 Conclusion 246 9 Portfolio Weights 253 9.1 Introduction 253 9.2 Ad Hoc Methods 255 9.3 Standard Mean-Variance Optimization 256 9.3.1 No Constraints 258 9.3.2 Short-Sale and Diversification Constraints 262 9.3.3 Sector or Industry Constraints 266 9.3.4 Trading-Volume Constraint 266 9.3.5 Risk-Adjusted Return 267 9.4 Benchmark 268 9.5 Ad Hoc Methods Again 268 9.6 Stratification 271 9.7 Factor-Exposure Targeting 273 9.8 Tracking-Error Minimization 276 9.8.1 Direct Computation 276 9.8.2 Tracking by Factor Exposure 278 9.8.3 Ghost Benchmark Tracking 280 9.8.4 Risk-Adjusted Tracking Error 281 9.9 Conclusion 282 Appendix 9A: Quadratic Programming 284 9A.1 Quadratic Programming with Equality Constraints 285 9A.2 A Numerical Example 287 9A.3 Quadratic Programming with Inequality Constraints 289 9A.4 A Numerical Example 293 10 Rebalancing and Transactions Costs 299 10.1 Introduction 299 10.2 The Rebalancing Decision 301 10.2.1 Rebalancing and Model Periodicity 301 10.2.2 Change in a and Other Parameters 302 10.3 Understanding Transactions Costs 303 10.4 Modeling Transactions Costs 304 10.5 Portfolio Construction with Transactions Costs 306 10.5.1 The Optimal Portfolio with Transactions Costs 306 10.5.2 The Tracking Portfolio with Transactions Costs 308 10.6 Dealing with Cash Flows 309 10.6.1 Reducing Transactions Cost Using Futures and ETFs 309 10.6.2 Rebalancing toward Optimal Target Weights 310 10.7 Conclusion 317 Appendix 10A: Approximate Solution to the Optimal Portfolio Problem 318 11 Tax Management 323 11.1 Introduction 323 11.2 Dividends, Capital Gains, and Capital Losses 324 11.3 Principles of Tax Management 327 11.4 Dividend Management 329 11.5 Tax-Lot Management 332 11.6 Tax-Lot Mathematics 334 11.7 Capital Gain and Loss Management 335 11.8 Loss Harvesting 338 11.8.1 Loss Harvesting and Reoptimizing 338 11.8.2 Loss Harvesting and Characteristic Matching 340 11.8.3 Loss Harvesting with a Benchmark 341 11.9 Gains from Tax Management 341 11.10 Conclusion 343 III x Mojo 347 12 Leverage 349 12.1 Introduction 349 12.2 Cash and Index Futures 351 12.2.1 Theoretical Bounds of Leverage 353 12.2.2 Leverage Mechanics 354 12.2.3 Expected Return and Risk 356 12.3 Stocks, Cash, and Index Futures 357 12.3.1 Theoretical Limits to Leverage 359 12.3.2 Leverage Mechanics 359 12.3.3 Expected Returns and Risk 360 12.4 Stocks, Cash, and Single-Stock Futures 362 12.4.1 Theoretical Limits of Leverage 363 12.4.2 Leverage Mechanics 364 12.4.3 Expected Returns, Risk, and a Mojo 367 12.5 Stocks, Cash, Individual Stocks, and Single-Stock and Basket Swaps 370 12.5.1 Margining Individual Stocks 371 12.5.2 Single-Stock and Basket Swaps 371 12.6 Stocks, Cash, and Options 373 12.7 Rebalancing 376 12.7.1 Cash and Futures 376 12.7.2 Stocks, Cash, and Futures 379 12.8 Liquidity Buffering 380 12.9 Leveraged Short 384 12.10 Conclusion 385 Appendix 12A: Fair Value Computations 387 Appendix 12B: Derivation of Equations (12.19), (12.20), and (12.21) 389 Appendix 12C: Tables of Futures Leverage Multipliers to Achieve Various Degrees of Leverage 391 13 Market Neutral 399 13.1 Introduction 399 13.2 Market-Neutral Construction 401 13.2.1 Security Selection 401 13.2.2 Dollar Neutrality 402 13.2.3 Beta Neutrality (a.k.a Risk-Factor Neutrality) 403 13.2.4 Market-Neutral Portfolio Out of a Long-Only Portfolio 406 13.3 Market Neutral's Mojo 406 13.4 The Mechanics of Market Neutral 409 13.4.1 Margin and Shorting 409 13.4.2 The Margin and Market Neutral 411 13.4.3 Sources of the Return 412 13.5 The Benefits and Drawbacks of Market Neutral 414 13.6 Rebalancing 419 13.7 General Long-Short 420 13.7.1 Long-Short 420 13.7.2 Equitization 421 13.7.3 Portable a 422 13.7.4 Pair Trading 424 13.8 Conclusion 428 14 Bayesian x 435 14.1 Introduction 435 14.2 The Basics of Bayesian Theory 436 14.3 Bayesian a Mojo 439 14.4 Quantifying Qualitative Information 440 14.4.1 Quantifying a Stock Screen 440 14.4.2 Quantifying a Stock Ranking 442 14.4.3 Quantifying the Buy and Sell Recommendations 443 14.5 The Z-Score-Based Prior 444 14.6 Scenario-Based Priors 445 14.7 Posterior Computation 448 14.8 The Information Criterion and Bayesian a 450 14.9 Conclusion 451 IV Performance Analysis 457 15 Performance Measurement and Attribution 459 15.1 Introduction 459 15.2 Measuring Returns 461 15.2.1 No Cash Flows 462 15.2.2 Inflows and Outflows 465 15.2.3 Measuring Returns for Market Neutral and Leveraged Portfolios 468 15.3 Measuring Risk 470 15.3.1 Standard Deviation 471 15.3.2 Semi-Standard Deviation 472 15.3.3 Tracking Error 473 15.3.4 CAPM 474 15.3.5 Value-at-Risk 476 15.3.6 Covariance and Correlation 477 15.4 Risk-Adjusted Performance Measurement 477 15.4.1 The Sharpe Ratio 479 15.4.2 The Information Ratio 480 15.4.3 The CAPM a and the Benchmark a 481 15.4.4 The Multifactor a 482 15.4.5 Practical Issues with Risk-Adjusted Measures 485 15.5 Performance Attribution 488 15.5.1 Classical Attribution 488 15.5.2 Multifactor QEPM Attribution 491 15.6 Conclusion 496 Appendix 15A: Style Analysis 497 Appendix 15B: Measures of Opportunity 503 Appendix 15C: Short Returns 507 Appendix 15D: Measuring Market Timing Ability 509 V Practical Application 519 16 The Backtesting Process 521 16.1 Introduction 521 16.2 The Data and Software 522 16.3 The Time Period 525 16.4 The Investment Universe and the Benchmark 531 16.4.1 U.S. Equity Benchmarks 532 16.4.2 A Comparison of the Major U.S. Equity Benchmarks 535 16.4.3 The Most Popular Benchmarks and Our Benchmarks 537 16.5 The Factors 542 16.6 The Stock-Return and Risk Models 554 16.7 Parameter Stability and the Rebalancing Frequency 556 16.8 Variations on the Baseline Portfolio 559 16.8.1 Transactions Costs 560 16.8.2 Taxes 562 16.8.3 Leverage 564 16.8.4 Market Neutral 565 16.9 Conclusion 566 Appendix 16A: Factor Formulas 567 17 The Portfolios' Performance 581 17.1 Introduction 581 17.2 The Performance of the Baseline Portfolios 582 17.2.1 The Fundamental Factor Model Performance 582 17.2.2 The Aggregate Z-Score Model Performance 585 17.2.3 The Economic Factor Model Performance 586 17.2.4 Performance Reports for Distribution 588 17.2.5 Performance Attribution for the Economic Factor Baseline Model 590 17.3 The Transactions Cost­Managed Portfolio Performance 596 17.4 The Tax-Managed Portfolio Performance 596 17.5 The Leveraged Portfolio Performance 599 17.6 The Market-Neutral Portfolio Performance 600 17.7 Conclusion 603 Contents of the CD 609 Glossary 611 Bibliography 619 Index 637

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