List of figures Preface Notation and typography 1 Introduction to financial time series
1.1 The object of interest
1.2 Approaching the dataset
1.3 Normality
1.4 Stationarity
1.4.1 Stationarity tests
1.5 Autocorrelation
1.5.1 ACF
1.5.2 PACF
1.6 Heteroskedasticity
1.7 Linear time series
1.8 Model selection
1.A How to import data
3.6 Alternative GARCH models
3.6.1 PARCH
3.6.2 NGARCH
3.6.3 NGARCHK
4 Multivariate GARCH models
4.1 Introduction
4.2 Multivariate GARCH
4.3 Direct generalizations of the univariate GARCH model of Bollerslev
4.3.1 Vech model
4.3.2 Diagonal vech model
4.3.3 BEKK model
4.3.4 Empirical application
Data description
Dvech model
4.4 Nonlinear combination of univariate GARCH—common features
4.4.1 Constant conditional correlation (CCC) GARCH
Empirical application
4.4.2 Dynamic conditional correlation (DCC) model
Dynamic conditional correlation Engle (DCCE) model
Empirical application
Dynamic conditional correlation Tse and Tsui (DCCT)
Prediction
4.5 Final remarks
5 Risk management
5.1 Introduction
5.2 Loss
5.3 Risk measures
5.4 VaR
5.4.1 VaR estimation
5.4.2 Parametric approach
5.4.3 Historical simulation
5.4.4 Monte Carlo simulation
5.4.5 Expected shortfall
5.5 Backtesting procedures
5.5.1 Unilevel VaR tests
The unconditional coverage test
The independence test
The conditional coverage test
The duration tests