The Basics of Financial Econometrics -- Contents -- Preface -- Acknowledgments -- About the Authors -- CHAPTER 1 Introduction -- FINANCIAL ECONOMETRICS AT WORK -- Step 1: Model Selection -- Step 2: Model Estimation -- Step 3: Model Testing -- THE DATA GENERATING PROCESS -- APPLICATIONS OF FINANCIAL ECONOMETRICS TO INVESTMENT MANAGEMENT -- Asset Allocation -- Portfolio Construction -- Portfolio Risk Management -- Key Points -- CHAPTER 2 Simple Linear Regression -- THE ROLE OF CORRELATION -- Stock Return Example -- REGRESSION MODEL: LINEAR FUNCTIONAL RELATIONSHIP BETWEEN TWO VARIABLES -- DISTRIBUTIONAL ASSUMPTIONS OF THE REGRESSION MODEL -- ESTIMATING THE REGRESSION MODEL -- Application to Stock Returns -- GOODNESS-OF-FIT OF THE MODEL -- Relationship between Coefficient of Determination and Correlation Coefficient -- TWO APPLICATIONS IN FINANCE -- Estimating the Characteristic Line of a Mutual Fund -- Controlling the Risk of a Stock Portfolio -- LINEAR REGRESSION OF A NONLINEAR RELATIONSHIP -- Linear Regression of Exponential Data -- KEY POINTS -- CHAPTER 3 Multiple Linear Regression -- THE MULTIPLE LINEAR REGRESSION MODEL -- ASSUMPTIONS OF THE MULTIPLE LINEAR REGRESSION MODEL -- ESTIMATION OF THE MODEL PARAMETERS -- DESIGNING THE MODEL -- DIAGNOSTIC CHECK AND MODEL SIGNIFICANCE -- Testing for the Significance of the Model -- Testing for the Significance of the Independent Variables -- The F-Test for Inclusion of Additional Variables -- APPLICATIONS TO FINANCE -- Estimation of Empirical Duration -- Predicting the 10-Year Treasury Yield -- Benchmark Selection: Sharpe Benchmarks -- Return-Based Style Analysis for Hedge Funds -- Rich/Cheap Analysis for the Mortgage Market -- Testing for Strong-Form Pricing Efficiency -- Tests of the Capital Asset Pricing Model -- Evidence for Multifactor Models -- KEY POINTS.

CHAPTER 4 Building and Testing a Multiple Linear Regression Model -- THE PROBLEM OF MULTICOLLINEARITY -- Procedures for Mitigating Multicollinearity -- MODEL BUILDING TECHNIQUES -- Stepwise Inclusion Regression Method -- Stepwise Exclusion Regression Method -- Standard Stepwise Regression Method -- TESTING THE ASSUMPTION OF THE MULTIPLE LINEAR REGRESSION MODEL -- Tests for Linearity -- Assumed Statistical Properties about the Error Term -- Tests for the Residuals Being Normally Distributed -- Tests For Constant Variance of the Error Term (Homoscedasticity) -- Absence of Autocorrelation of the Residuals -- KEY POINTS -- CHAPTER 5 Introduction to Time Series Analysis -- WHAT IS A TIME SERIES? -- DECOMPOSITION OF TIME SERIES -- Application to S&P 500 Index Returns -- REPRESENTATION OF TIME SERIES WITH DIFFERENCE EQUATIONS -- APPLICATION: THE PRICE PROCESS -- Random Walk -- Error Correction -- KEY POINTS -- CHAPTER 6 Regression Models with Categorical Variables -- INDEPENDENT CATEGORICAL VARIBLES -- Statistical Tests -- DEPENDENT CATEGORICAL VARIABLES -- Linear Probability Model -- Probit Regression Model -- Logit Regression Model -- KEY POINTS -- CHAPTER 7 Quantile Regressions -- LIMITATIONS OF CLASSICAL REGRESSION ANALYSIS -- PARAMETER ESTIMATION -- QUANTILE REGRESSION PROCESS -- APPLICATION OF QUANTILE REGRESSION IN FINANCE -- Determining a Portfolio Manager's Style -- Determining the Factors That Impact Capital Structure -- KEY POINTS -- CHAPTER 8 Robust Regressions -- ROBUST ESTIMATORS OF REGRESSIONS -- Robust Regressions Based on M-Estimators -- ILLUSTRATION: ROBUSTNESS OF THE CORPORATE BOND YIELD SPREAD MODEL -- ROBUST ESTIMATION OF COVARIAVCE AND CORRELATION MATRICES -- APPLICATION -- KEY POINTS -- CHAPTER 9 Autoregressive Moving Average Models -- AUTOREGRESSIVE MODELS -- Partial Autocorrelation -- Information Criterion -- MOVING AVERAGE MODELS.

AUTOGRESSIVE MOVING AVERAGE MODELS -- ARMA MODELING TO FORECAST S&P 500 WEEKLY INDEX RETURNS -- VECTOR AUTOGRESSIVE MODELS -- KEY POINTS -- CHAPTER 10 Cointegration -- STATIONARY AND NONSTATIONARY VARIABLES AND COINTEGRATION -- TESTING FOR COINTEGRATION -- Engle-Granger Cointegration Tests -- Johansen-Juselius Cointegration Test -- KEY POINTS -- CHAPTER 11 Autoregressive Heteroscedasticity Model and Its Variants -- ESTIMATING AND FORECASTING VOLATILITY -- ARCH BEHAVIOR -- Modeling ARCH Behavior -- ARCH in the Mean Model -- GARCH MODEL -- WHAT DO ARCH/GARCH MODELS REPRESENT? -- UNIVARIATE EXTENSIONS OF GARCH MODELING -- ESTIMATES OF ARCH/GARCH MODELS -- APPLICATION OF GARCH MODELS TO OPTION PRICING -- MULTIVARIATE EXTENSIONS OF ARCH/GARCH MODELING -- KEY POINTS -- CHAPTER 12 Factor Analysis and Principal Components Analysis -- ASSUMPTIONS OF LINEAR REGRESSION -- BASIC CONCEPTS OF FACTOR MODELS -- ASSUMPTIONS AND CATEGORIZATION OF FACTOR MODELS -- SIMILARITIES AND DIFFERENCES BETWEEN FACTOR MODELS AND LINEAR REGRESSION -- PROPERT IES OF FACTOR MODELS -- ESTIMAT ION OF FACTOR MODELS -- Problem of Factor Indeterminacy -- Estimating the Number of Factors -- Estimating the Model's Parameters -- Estimation of Factors -- Other Types of Factor Models -- PRINCIPAL COMPONENTS ANALYSIS -- Step-by-Step PCA -- The Process of PCA -- DIFFERENCES BETWEEN FACTOR ANALYSIS AND PCA -- APPROXIMATE (LARGE) FACTOR MODELS -- APPROXIMATE FACTOR MODELS AND PCA -- KEY POINTS -- CHAPTER 13 Model Estimation -- STATISTICAL ESTIMATION AND TESTING -- ESTIMATION METHODS -- LEAST-SQUARES ESTIMATION METHOD -- Ordinary Least Squares Method -- Weighted Least Squares Method -- Generalized Least Squares Method -- THE MAXIMUM LIKELIHOOD ESTIMATION METHOD -- Application of MLE to Regression Models -- Application of MLE to Regression Models -- Application of MLE to Factor Models.

INSTRUMENTAL VARIABLES -- METHOD OF MOMENTS -- Generalized Method of Moments -- THE M-ESTIMATION METHOD AND M-ESTIMATORS -- KEY POINTS -- CHAPTER 14 Model Selection -- PHYSICS AND ECONOMICS: TWO WAYS OF MAKING SCIENCE -- MODEL COMPLEXITY AND SAMPLE SIZE -- DATA SNOOPING -- SURVIVORSHIP BIASES AND OTHER SAMPLE DEFECTS -- Moving Training Windows -- MODEL RISK -- MODEL SELECTION IN A NUTSHELL -- KEY POINTS -- CHAPTER 15 Formulating and Implementing Investment Strategies Using Financial Econometrics -- THE QUANTITATIVE RESEARCH PROCESS -- Develop an Ex Ante Justification Based on Financial Economic Theory -- Select a Sample Free from Survivorship Bias -- Select a Methodology to Estimate the Model -- Trade-Off between Better Estimations and Prediction Errors -- Influence of Emotions -- Statistical Significance Does Not Guarantee Alpha -- INVESTMENT STRATEGY PROCESS -- A Model To Estimate Expected Returns -- Independent Risk Control -- KEY POINTS -- Appendix A Descriptive Statistics -- BASIC DATA ANALYSIS -- Cross-Sectional Data and Time Series Data -- Frequency Distributions -- Empirical Cumulative Frequency Distribution -- Continuous versus Discrete Variables -- Cumulative Frequency Distributions -- MEASURES OF LOCATION AND SPREAD -- Parameters versus Statistics -- Center and Location -- Variation -- MULTIVARIATE VARIABLES AND DISTRIBUTIONS -- Frequencies -- Marginal Distributions -- Graphical Representation -- Conditional Distribution -- Independence -- Covariance -- Correlation -- Contingency Coefficient -- Appendix B Continuous Probability Distributions Commonly Used in Financial Econometrics -- NORMAL DISTRIBUTION -- Properties of the Normal Distribution -- CHI-SQUARE DISTRIBUTION -- STUDENT'S t-DISTRIBUTION -- F -DISTRIBUTION -- α-STABLE DISTRIBUTION -- Appendix C Inferential Statistics -- POINT ESTIMATORS -- Sample, Statistic, and Estimator.

Quality Criteria of Estimators -- Large-Sample Criteria -- CONFIDENCE INTERVALS -- Confidence Level and Confidence interval -- HYPOTHESIS TESTING -- Hypotheses -- Error Types -- Test Size -- The p-Value -- Quality Criteria of a Test -- Appendix D Fundamentals of Matrix Algebra -- VECTORS AND MATRICES DEFINED -- Vectors -- Matrices -- SQUARE MATRICES -- DETERMINANTS -- SYSTEMS OF LINEAR EQUATIONS -- LINEAR INDEPENDENCE AND RANK -- VECTOR AND MATRIX OPERATIONS -- Vector Operations -- Matrix Operations -- EIGENVALUES AND EIGENVECTORS -- APPENDIX E Model Selection Criterion: AIC and BIC -- AKAIKE INFORMATION CRITERION -- BAYESIAN INFORMATION CRITERION -- Appendix F Robust Statistics -- ROBUST STATISTICS DEFINED -- QUALITATIVE AND QUANTITATIVE ROBUSTNESS -- RESISTANT ESTIMATORS -- Breakdown Bound -- Rejection Point -- Gross Error Sensitivity -- Local Shift Sensitivity -- Winsor's Principle -- M-ESTIMATORS -- THE LEAST MEDIAN OF SQUARES ESTIMATOR -- THE LEAST TRIMMED OF SQUARES ESTIMATOR -- ROBUST ESTIMATORS OF THE CENTER -- ROBUST ESTIMATORS OF THE SPREAD -- ILLUSTRATION OF ROBUST STATISTICS -- Index.