
Garch Models: Structure, Statistical Inference and Financial Applications
by Christian Francq (Laboratory EQUIPPE, Lille, France); Jean-Michel Zakoian (Laboratory EQUIPPE, Lille, France)Rent Textbook
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Summary
Table of Contents
Preface | |
Notation | |
Classical Time Series Models and Financial Series | |
Stationary Processes | |
ARMA and ARIMA Models | |
Financial Series | |
Random Variance Models | |
Bibliographical Notes | |
Exercises | |
Univariate GARCH Models | |
GARCH( p, q ) Processes | |
Definitions and Representations | |
Stationarity Study | |
ARCH ( ∞ ) Representation | |
Properties of the Marginal Distribution | |
Autocovariances of the Squares of a GARCH | |
Theoretical Predictions | |
Bibliographical Notes | |
Exercises | |
Mixing | |
Markov Chains with Continuous State Space | |
Mixing Properties of GARCH Processes | |
Bibliographical Notes | |
Exercises | |
Temporal Aggregation and Weak GARCH Models | |
Temporal Aggregation of GARCH Processes | |
Weak GARCH | |
Aggregation of Strong GARCH Processes in the Weak GARCH Class | |
Bibliographical Notes | |
Exercises | |
Statistical Inference | |
Identification | |
Autocorrelation Check for White Noise | |
Identifying the ARMA Orders of an ARMA-GARCH | |
Identifying the GARCH Orders of an ARMA-GARCH Model | |
Lagrange Multiplier Test for Conditional Homoscedasticity | |
Application to Real Series | |
Bibliographical Notes | |
Exercises | |
Estimating ARCH Models by Least Squares | |
Estimation of ARCH( q ) models by Ordinary Least Squares | |
Estimation of ARCH( q ) Models by Feasible Generalized Least Squares | |
Estimation by Constrained Ordinary Least Squares | |
Bibliographical Notes | |
Exercises | |
Estimating GARCH Models by Quasi-Maximum Likelihood | |
Conditional Quasi-Likelihood | |
Estimation of ARMA-GARCH Models by Quasi-Maximum Likelihood | |
Application to Real Data | |
Proofs of the Asymptotic Results | |
Bibliographical Notes | |
Exercises | |
Tests Based on the Likelihood | |
Test of the Second-Order Stationarity Assumption | |
Asymptotic Distribution of the QML When ¿ 0 is at the Boundary | |
Significance of the GARCH Coefficients | |
Diagnostic Checking with Portmanteau Tests | |
Application: Is the GARCH(1,1) Model Overrepresented? | |
Proofs of the Main Results | |
Bibliographical Notes | |
Exercises | |
Optimal Inference and Alternatives to the QMLE | |
Maximum Likelihood Estimator | |
Maximum Likelihood Estimator with Misspecified Density | |
Alternative Estimation Methods | |
Bibliographical Notes | |
Exercises | |
Extensions and Applications | |
Asymmetries | |
Exponential GARCH Model | |
Threshold GARCH Model | |
Asymmetric Power GARCH Model | |
Other Asymmetric GARCH Models | |
A GARCH Model with Contemporaneous Conditional Asymmetry | |
Empirical Comparisons of Asymmetric GARCH Formulations | |
Bibliographical Notes | |
Exercises | |
Multivariate GARCH Processes | |
Multivariate Stationary Processes | |
Multivariate GARCH Models | |
Stationarity | |
Estimation of the CCC Model | |
Bibliographical Notes | |
Exercises | |
Financial Applications | |
Relation between GARCH and Continuous-Time Models | |
Option Pricing | |
Value at Risk and Other Risk Measures | |
Bibliographical Notes | |
Exercises | |
Appendices | |
Ergodicity, Martingales, Mixing | |
Ergodicity | |
Martingale Increments | |
Mixing | |
Autocorrelation and Partial Autocorrelation | |
Partial Autocorrelation | |
Generalized Bartlett Formula for Nonlinear Processes | |
Solutions to the Exercises | |
Problems | |
References | |
Index | |
Table of Contents provided by Publisher. All Rights Reserved. |
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