What is included with this book?
Preface | p. xi |
About the Authors | p. xv |
Introduction | p. 1 |
In Praise of Mathematical Finance | p. 3 |
Studies of the Use of Quantitative Equity Management | p. 9 |
Looking Ahead for Quantitative Equity Investing | p. 45 |
Financial Econometrics I: Linear Regressions | p. 47 |
Historical Notes | p. 47 |
Covariance and Correlation | p. 49 |
Regressions, Linear Regressions, and Projections | p. 61 |
Multivariate Regression | p. 76 |
Quantile Regressions | p. 78 |
Regression Diagnostic | p. 80 |
Robust Estimation of Regressions | p. 83 |
Classification and Regression Trees | p. 96 |
Summary | p. 99 |
Financial Econometrics II: Time Series | p. 101 |
Stochastic Processes | p. 101 |
Time Series | p. 102 |
Stable Vector Autoregressive Processes | p. 110 |
Integrated and Cointegrated Variables | p. 114 |
Estimation of Stable Vector Autoregressive (VAR) Models | p. 120 |
Estimating the Number of Lags | p. 137 |
Autocorrelation and Distributional Properties of Residuals | p. 139 |
Stationary Autoregressive Distributed Lag Models | p. 140 |
Estimation of Nonstationary VAR Models | p. 141 |
Estimation with Canonical Correlations | p. 151 |
Estimation with Principal Component Analysis | p. 153 |
Estimation with the Eigenvalues of the Companion Matrix | p. 154 |
Nonlinear Models in Finance | p. 155 |
Causality | p. 156 |
Summary | p. 157 |
Common Pitfalls in Financial Modeling | p. 159 |
Theory and Engineering | p. 159 |
Engineering and Theoretical Science | p. 161 |
Engineering and Product Design in Finance | p. 163 |
Learning, Theoretical, and Hybrid Approaches to Portfolio Management | p. 164 |
Sample Biases | p. 165 |
The Bias in Averages | p. 167 |
Pitfalls in Choosing from Large Data Sets | p. 170 |
Time Aggregation of Models and Pitfalls in the Selection of Data Frequency | p. 173 |
Model Risk and its Mitigation | p. 174 |
Summary | p. 193 |
Factor Models and their Estimation | p. 195 |
The Notion of Factors | p. 195 |
Static Factor Models | p. 196 |
Factor Analysis and Principal Components Analysis | p. 205 |
Why Factor Models of Returns | p. 219 |
Approximate Factor Models of Returns | p. 221 |
Dynamic Factor Models | p. 222 |
Summary | p. 239 |
Factor-Based Trading Strategies I: Factor Construction and Analysis | p. 243 |
Factor-Based Trading | p. 245 |
Developing Factor-Based Trading Strategies | p. 247 |
Risk to Trading Strategies | p. 249 |
Desirable Properties of Factors | p. 251 |
Sources for Factors | p. 251 |
Building Factors from Company Characteristics | p. 253 |
Working with Data | p. 253 |
Analysis of Factor Data | p. 261 |
Summary | p. 266 |
Factor-Based Trading Strategies II: Cross-Sectional Models and Trading Strategies | p. 269 |
Cross-Sectional Methods for Evaluation of Factor Premiums | p. 270 |
Factor Models | p. 278 |
Performance Evaluation of Factors | p. 288 |
Model Construction Methodologies for a Factor-Based Trading Strategy | p. 295 |
Backtesting | p. 306 |
Backtesting Our Factor Trading Strategy | p. 308 |
Summary | p. 309 |
Portfolio Optimization: Basic Theory and Practice | p. 313 |
Mean-Variance Analysis: Overview | p. 314 |
Classical Framework for Mean-Variance Optimization | p. 317 |
Mean-Variance Optimization with a Risk-Free Asset | p. 321 |
Portfolio Constraints Commonly Used in Practice | p. 327 |
Estimating the Inputs Used in Mean-Variance Optimization: Expected Return and Risk | p. 333 |
Portfolio Optimization with Other Risk Measures | p. 342 |
Summary | p. 357 |
Portfolio Optimization: Bayesian Techniques and the Black-Litterman Model | p. 361 |
Practical Problems Encountered in Mean-Variance Optimization | p. 362 |
Shrinkage Estimation | p. 369 |
The Black-Litterman Model | p. 373 |
Summary | p. 394 |
Robust Portfolio Optimization | p. 395 |
Robust Mean-Variance Formulations | p. 396 |
Using Robust Mean-Variance Portfolio Optimization in Practice | p. 411 |
Some Practical Remarks on Robust Portfolio Optimization Models | p. 416 |
Summary | p. 418 |
Transaction Costs and Trade Execution | p. 419 |
A Taxonomy of Transaction Costs | p. 420 |
Liquidity and Transaction Costs | p. 427 |
Market Impact Measurements and Empirical Findings | p. 430 |
Forecasting and Modeling Market Impact | p. 433 |
Incorporating Transaction Costs in Asset-Allocation Models | p. 439 |
Integrated Portfolio Management: Beyond Expected Return and Portfolio Risk | p. 444 |
Summary | p. 446 |
Investment Management and Algorithmic Trading | p. 449 |
Market Impact and the Order Book | p. 450 |
Optimal Execution | p. 452 |
Impact Models | p. 455 |
Popular Algorithmic Trading Strategies | p. 457 |
What Is Next? | p. 465 |
Some Comments about the High-Frequency Arms Race | p. 467 |
Summary | p. 470 |
Data Descriptions and Factor Definitions | p. 473 |
The MSCI World Index | p. 473 |
One-Month LIBOR | p. 482 |
The Compustat Point-in-Time, IBES Consensus Databases and Factor Definitions | p. 483 |
Summary of Well-Known Factors and Their Underlying Economic Rationale | p. 487 |
Review of Eigenvalues and Eigenvectors | p. 493 |
The SWEEP Operator | p. 494 |
Index | p. 497 |
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