CHAPTER 1
Financial Econometrics: Scope and Methods  1
The Data Generating Process  3
Financial Econometrics at Work  7
Time Horizon of Models  10
Applications 12
Appendix: Investment Management Process  16
Concepts Explained in this Chapter (in order of presentation)  22
CHAPTER 2
Review of Probability and Statistics  25
Concepts of Probability  25
Principles of Estimation  58
Bayesian Modeling  69
Appendix A: Information Structures  72
Appendix B: Filtration  74
Concepts Explained in this Chapter (in order of presentation) 75
CHAPTER 3
Regression Analysis: Theory and Estimation  79
The Concept of Dependence  79
Regressions and Linear Models  85
Estimation of Linear Regressions  90
Sampling Distributions of Regressions  96
Determining the Explanatory Power of a Regression  97
Using Regression Analysis in Finance  99
Stepwise Regression  114
Nonnormality and Autocorrelation of the Residuals  121
Pitfalls of Regressions  123
Concepts Explained in this Chapter (in order of presentation)  125
CHAPTER 4
Selected Topics in Regression Analysis  127
Categorical and Dummy Variables in Regression Models  127
Constrained Least Squares  151
The Method of Moments and its Generalizations  163
Concepts Explained in this Chapter (in order of presentation)  167
CHAPTER 5
Regression Applications in Finance  169
Applications to the Investment Management Process  169
A Test of Strong-Form Pricing Efficiency  174
Tests of the CAPM  175
Using the CAPM to Evaluate Manager Performance: The Jensen Measure  179
Evidence for Multifactor Models  180
Benchmark Selection: Sharpe Benchmarks  184
Return-Based Style Analysis for Hedge Funds  186
Hedge Fund Survival  191
Bond Portfolio Applications  192
Concepts Explained in this Chapter (in order of presentation)  199
CHAPTER 6
Modeling Univariate Time Series  201
Difference Equations  201
Terminology and Definitions  207
Stationarity and Invertibility of ARMA Processes  214
Linear Processes  219
Identification Tools 223
Concepts Explained in this Chapter (in order of presentation)  239
CHAPTER 7
Approaches to ARIMA Modeling and Forecasting  241
Overview of Box-Jenkins Procedure  242
Identification of Degree of Differencing  244
Identification of Lag Orders  250
Model Estimation  253
Diagnostic Checking  262
Forecasting 271
Concepts Explained in this Chapter (in order of presentation)  277
CHAPTER 8
Autoregressive Conditional Heteroskedastic Models  279
ARCH Process  280
GARCH Process  284
Estimation of the GARCH Models 289
Stationary ARMA-GARCH Models  293

Lagrange Multiplier Test  294
Variants of the GARCH Model  298
GARCH Model with Student’s t-Distributed Innovations  299
Multivariate GARCH Formulations  314
Appendix: Analysis of the Properties of the GARCH(1,1) Model  316
Concepts Explained in this Chapter (in order of presentation)  319
CHAPTER 9
Vector Autoregressive Models I  321
VAR Models Defined  321
Stationary Autoregressive Distributed Lag Models  334
Vector Autoregressive Moving Average Models  335
Forecasting with VAR Models  338
Appendix: Eigenvectors and Eigenvalues  339
Concepts Explained in this Chapter (in order of presentation)  341
CHAPTER 10
Vector Autoregressive Models II  343
Estimation of Stable VAR Models  343
Estimating the Number of Lags  357
Autocorrelation and Distributional Properties of Residuals  359
VAR Illustration  360
Concepts Explained in this Chapter (in order of presentation)  372
CHAPTER 11
Cointegration and State Space Models  373
Cointegration 373
Error Correction Models  381
Theory and Methods of Estimation of Nonstationary VAR Models  385
State-Space Models  398
Concepts Explained in this Chapter (in order of presentation)  404
CHAPTER 12
Robust Estimation  407
Robust Statistics  407
Robust Estimators of Regressions  417
Illustration: Robustness of the Corporate Bond Yield Spread Model  421
Concepts Explained in this Chapter (in order of presentation)  428
CHAPTER 13
Principal Components Analysis and Factor Analysis  429
Factor Models  429
Principal Components Analysis  436
Factor Analysis  450
PCA and Factor Analysis Compared  461
Concepts Explained in this Chapter (in order of presentation)  464
CHAPTER 14
Heavy-Tailed and Stable Distributions in Financial Econometrics  465
Basic Facts and Definitions of Stable Distributions  468
Properties of Stable Distributions  475
Estimation of the Parameters of the Stable Distribution  479
Applications to German Stock Data  485
Appendix: Comparing Probability Distributions  487
Concepts Explained in this Chapter (in order of presentation)  494
CHAPTER 15
ARMA and ARCH Models with Infinite-Variance Innovations  495
Infinite Variance Autoregressive Processes  495
Stable GARCH Models  501
Estimation for the Stable GARCH Model  507
Prediction of Conditional Densities  513
Concepts Explained in this Chapter (in order of presentation)  516
APPENDIX
Monthly Returns for 20 Stocks: December 2000–November 2005  517
INDEX 525